Speech synthesis - Knowledge

1518: 1736:. The software was licensed from third-party developers Joseph Katz and Mark Barton (later, SoftVoice, Inc.) and was featured during the 1984 introduction of the Macintosh computer. This January demo required 512 kilobytes of RAM memory. As a result, it could not run in the 128 kilobytes of RAM the first Mac actually shipped with. So, the demo was accomplished with a prototype 512k Mac, although those in attendance were not told of this and the synthesis demo created considerable excitement for the Macintosh. In the early 1990s Apple expanded its capabilities offering system wide text-to-speech support. With the introduction of faster PowerPC-based computers they included higher quality voice sampling. Apple also introduced 408: 1650:. The program was available for non-Macintosh Apple computers (including the Apple II, and the Lisa), various Atari models and the Commodore 64. The Apple version preferred additional hardware that contained DACs, although it could instead use the computer's one-bit audio output (with the addition of much distortion) if the card was not present. The Atari made use of the embedded POKEY audio chip. Speech playback on the Atari normally disabled interrupt requests and shut down the ANTIC chip during vocal output. The audible output is extremely distorted speech when the screen is on. The Commodore 64 made use of the 64's embedded SID audio chip. 980:; however, many concatenative systems also have rules-based components. Many systems based on formant synthesis technology generate artificial, robotic-sounding speech that would never be mistaken for human speech. However, maximum naturalness is not always the goal of a speech synthesis system, and formant synthesis systems have advantages over concatenative systems. Formant-synthesized speech can be reliably intelligible, even at very high speeds, avoiding the acoustic glitches that commonly plague concatenative systems. High-speed synthesized speech is used by the visually impaired to quickly navigate computers using a 567: 1894:, a text-to-speech utility for people who have visual impairment. Third-party programs such as JAWS for Windows, Window-Eyes, Non-visual Desktop Access, Supernova and System Access can perform various text-to-speech tasks such as reading text aloud from a specified website, email account, text document, the Windows clipboard, the user's keyboard typing, etc. Not all programs can use speech synthesis directly. Some programs can use plug-ins, extensions or add-ons to read text aloud. Third-party programs are available that can read text from the system clipboard. 574: 68: 1208:. The company states its software is built to adjust the intonation and pacing of delivery based on the context of language input used. It uses advanced algorithms to analyze the contextual aspects of text, aiming to detect emotions like anger, sadness, happiness, or alarm, which enables the system to understand the user's sentiment, resulting in a more realistic and human-like inflection. Other features include multilingual speech generation and long-form content creation with contextually-aware voices. 523:(LSP) method for high-compression speech coding, while at NTT. From 1975 to 1981, Itakura studied problems in speech analysis and synthesis based on the LSP method. In 1980, his team developed an LSP-based speech synthesizer chip. LSP is an important technology for speech synthesis and coding, and in the 1990s was adopted by almost all international speech coding standards as an essential component, contributing to the enhancement of digital speech communication over mobile channels and the internet. 832:(DSP) to the recorded speech. DSP often makes recorded speech sound less natural, although some systems use a small amount of signal processing at the point of concatenation to smooth the waveform. The output from the best unit-selection systems is often indistinguishable from real human voices, especially in contexts for which the TTS system has been tuned. However, maximum naturalness typically require unit-selection speech databases to be very large, in some systems ranging into the 1324:

also be read as "one three two five", "thirteen twenty-five" or "thirteen hundred and twenty five". A TTS system can often infer how to expand a number based on surrounding words, numbers, and punctuation, and sometimes the system provides a way to specify the context if it is ambiguous. Roman numerals can also be read differently depending on context. For example, "Henry VIII" reads as "Henry the Eighth", while "Chapter VIII" reads as "Chapter Eight".

2367: 877:. Diphone synthesis suffers from the sonic glitches of concatenative synthesis and the robotic-sounding nature of formant synthesis, and has few of the advantages of either approach other than small size. As such, its use in commercial applications is declining, although it continues to be used in research because there are a number of freely available software implementations. An early example of Diphone synthesis is a teaching robot, 1346: 193: 1814: 1316:" to aid in disambiguating homographs. This technique is quite successful for many cases such as whether "read" should be pronounced as "red" implying past tense, or as "reed" implying present tense. Typical error rates when using HMMs in this fashion are usually below five percent. These techniques also work well for most European languages, although access to required training 1597:). The synthesizer uses a variant of linear predictive coding and has a small in-built vocabulary. The original intent was to release small cartridges that plugged directly into the synthesizer unit, which would increase the device's built-in vocabulary. However, the success of software text-to-speech in the Terminal Emulator II cartridge canceled that plan. 1439:

approach works on any input, but the complexity of the rules grows substantially as the system takes into account irregular spellings or pronunciations. (Consider that the word "of" is very common in English, yet is the only word in which the letter "f" is pronounced .) As a result, nearly all speech synthesis systems use a combination of these approaches.

1844:", which allowed command-line users to redirect text output to speech. Speech synthesis was occasionally used in third-party programs, particularly word processors and educational software. The synthesis software remained largely unchanged from the first AmigaOS release and Commodore eventually removed speech synthesis support from AmigaOS 2.1 onward. 1489:, reported that listeners to voice recordings could determine, at better than chance levels, whether or not the speaker was smiling. It was suggested that identification of the vocal features that signal emotional content may be used to help make synthesized speech sound more natural. One of the related issues is modification of the 1447:

loanwords, whose pronunciations are not obvious from their spellings. On the other hand, speech synthesis systems for languages like English, which have extremely irregular spelling systems, are more likely to rely on dictionaries, and to use rule-based methods only for unusual words, or words that are not in their dictionaries.

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In the early 1980s, TI was known as a pioneer in speech synthesis, and a highly popular plug-in speech synthesizer module was available for the TI-99/4 and 4A. Speech synthesizers were offered free with the purchase of a number of cartridges and were used by many TI-written video games (games offered

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The consistent evaluation of speech synthesis systems may be difficult because of a lack of universally agreed objective evaluation criteria. Different organizations often use different speech data. The quality of speech synthesis systems also depends on the quality of the production technique (which

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used to create convincing speech sentences that sound like specific people saying things they did not say. This technology was initially developed for various applications to improve human life. For example, it can be used to produce audiobooks, and also to help people who have lost their voices (due

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Concatenative synthesis is based on the concatenation (stringing together) of segments of recorded speech. Generally, concatenative synthesis produces the most natural-sounding synthesized speech. However, differences between natural variations in speech and the nature of the automated techniques for

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Content creators have used voice cloning tools to recreate their voices for podcasts, narration, and comedy shows. Publishers and authors have also used such software to narrate audiobooks and newsletters. Another area of application is AI video creation with talking heads. Webapps and video editors

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Text-to-speech (TTS) refers to the ability of computers to read text aloud. A TTS engine converts written text to a phonemic representation, then converts the phonemic representation to waveforms that can be output as sound. TTS engines with different languages, dialects and specialized vocabularies

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Deciding how to convert numbers is another problem that TTS systems have to address. It is a simple programming challenge to convert a number into words (at least in English), like "1325" becoming "one thousand three hundred twenty-five". However, numbers occur in many different contexts; "1325" may

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Domain-specific synthesis concatenates prerecorded words and phrases to create complete utterances. It is used in applications where the variety of texts the system will output is limited to a particular domain, like transit schedule announcements or weather reports. The technology is very simple to

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of recorded data, representing dozens of hours of speech. Also, unit selection algorithms have been known to select segments from a place that results in less than ideal synthesis (e.g. minor words become unclear) even when a better choice exists in the database. Recently, researchers have proposed

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In the 2010s, Singing synthesis technology has taken advantage of the recent advances in artificial intelligence—deep listening and machine learning to better represent the nuances of the human voice. New high fidelity sample libraries combined with digital audio workstations facilitate editing in

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Each approach has advantages and drawbacks. The dictionary-based approach is quick and accurate, but completely fails if it is given a word which is not in its dictionary. As dictionary size grows, so too does the memory space requirements of the synthesis system. On the other hand, the rule-based

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Because these systems are limited by the words and phrases in their databases, they are not general-purpose and can only synthesize the combinations of words and phrases with which they have been preprogrammed. The blending of words within naturally spoken language however can still cause problems

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speech synthesizer chip on a removable cartridge. The Narrator had 2kB of Read-Only Memory (ROM), and this was utilized to store a database of generic words that could be combined to make phrases in Intellivision games. Since the Orator chip could also accept speech data from external memory, any

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is stored by the program. Determining the correct pronunciation of each word is a matter of looking up each word in the dictionary and replacing the spelling with the pronunciation specified in the dictionary. The other approach is rule-based, in which pronunciation rules are applied to words to

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Similarly, abbreviations can be ambiguous. For example, the abbreviation "in" for "inches" must be differentiated from the word "in", and the address "12 St John St." uses the same abbreviation for both "Saint" and "Street". TTS systems with intelligent front ends can make educated guesses about

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have a very regular writing system, and the prediction of the pronunciation of words based on their spellings is quite successful. Speech synthesis systems for such languages often use the rule-based method extensively, resorting to dictionaries only for those few words, like foreign names and

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implement, and has been in commercial use for a long time, in devices like talking clocks and calculators. The level of naturalness of these systems can be very high because the variety of sentence types is limited, and they closely match the prosody and intonation of the original recordings.

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fine detail, such as shifting of formats, adjustment of vibrato, and adjustments to vowels and consonants. Sample libraries for various languages and various accents are available. With today's advancements in vocal synthesis, artists sometimes use sample libraries in lieu of backing singers.

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Speech synthesis techniques are also used in entertainment productions such as games and animations. In 2007, Animo Limited announced the development of a software application package based on its speech synthesis software FineSpeech, explicitly geared towards customers in the entertainment

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More recent synthesizers, developed by Jorge C. Lucero and colleagues, incorporate models of vocal fold biomechanics, glottal aerodynamics and acoustic wave propagation in the bronchi, trachea, nasal and oral cavities, and thus constitute full systems of physics-based speech simulation.

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Naturalness describes how closely the output sounds like human speech, while intelligibility is the ease with which the output is understood. The ideal speech synthesizer is both natural and intelligible. Speech synthesis systems usually try to maximize both characteristics.

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Text-to-speech is also used in second language acquisition. Voki, for instance, is an educational tool created by Oddcast that allows users to create their own talking avatar, using different accents. They can be emailed, embedded on websites or shared on social media.

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Speech synthesis has long been a vital assistive technology tool and its application in this area is significant and widespread. It allows environmental barriers to be removed for people with a wide range of disabilities. The longest application has been in the use of

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Despite the American English phoneme limitation, an unofficial version with multilingual speech synthesis was developed. This made use of an enhanced version of the translator library which could translate a number of languages, given a set of rules for each language.

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Early electronic speech-synthesizers sounded robotic and were often barely intelligible. The quality of synthesized speech has steadily improved, but as of 2016 output from contemporary speech synthesis systems remains clearly distinguishable from actual human speech.

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in the late 1940s and completed it in 1950. There were several different versions of this hardware device; only one currently survives. The machine converts pictures of the acoustic patterns of speech in the form of a spectrogram back into sound. Using this device,

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that all require expansion into a phonetic representation. There are many spellings in English which are pronounced differently based on context. For example, "My latest project is to learn how to better project my voice" contains two pronunciations of "project".

1631: 1152: 584: 1924: 1805: 1660: 1840:. The synthesis system was divided into a translator library which converted unrestricted English text into a standard set of phonetic codes and a narrator device which implemented a formant model of speech generation.. AmigaOS also featured a high-level " 1630: 1149: 1923: 1716: 1703: 1659: 1211:

The DNN-based speech synthesizers are approaching the naturalness of the human voice. Examples of disadvantages of the method are low robustness when the data are not sufficient, lack of controllability and low performance in auto-regressive models.

88: 87: 1164:(DNN) to produce artificial speech from text (text-to-speech) or spectrum (vocoder). The deep neural networks are trained using a large amount of recorded speech and, in the case of a text-to-speech system, the associated labels and/or input text. 1574: 543: 1174:—hundreds of voices are trained concurrently rather than sequentially, decreasing the required training time and enabling the model to learn and generalize shared emotional context, even for voices with no exposure to such emotional context. The 1148: 530:

was released, and was one of the first Speech Synthesis systems. It consisted of a stand-alone computer hardware and a specialized software that enabled it to read Italian. A second version, released in 1978, was also able to sing Italian in an

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additional words or phrases needed could be stored inside the cartridge itself. The data consisted of strings of analog-filter coefficients to modify the behavior of the chip's synthetic vocal-tract model, rather than simple digitized samples.

1802: 1764:), the user can choose out of a wide range list of multiple voices. VoiceOver voices feature the taking of realistic-sounding breaths between sentences, as well as improved clarity at high read rates over PlainTalk. Mac OS X also includes 1632: 1801: 1456:

may involve analogue or digital recording) and on the facilities used to replay the speech. Evaluating speech synthesis systems has therefore often been compromised by differences between production techniques and replay facilities.

1925: 1661: 1713: 1700: 1075:. The system, first marketed in 1994, provides full articulatory-based text-to-speech conversion using a waveguide or transmission-line analog of the human oral and nasal tracts controlled by Carré's "distinctive region model". 1150: 5042: 1699: 1712: 540: 169:

provides the largest output range, but may lack clarity. For specific usage domains, the storage of entire words or sentences allows for high-quality output. Alternatively, a synthesizer can incorporate a model of the

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to throat disease or other medical problems) to get them back. Commercially, it has opened the door to several opportunities. This technology can also create more personalized digital assistants and natural-sounding

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In 1976, Computalker Consultants released their CT-1 Speech Synthesizer. Designed by D. Lloyd Rice and Jim Cooper, it was an analog synthesizer built to work with microcomputers using the S-100 bus standard.

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was visiting his friend and colleague John Pierce at the Bell Labs Murray Hill facility. Clarke was so impressed by the demonstration that he used it in the climactic scene of his screenplay for his novel

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of the language: for example, Spanish has about 800 diphones, and German about 2500. In diphone synthesis, only one example of each diphone is contained in the speech database. At runtime, the target

5511:"Hot AI startup ElevenLabs, founded by ex-Google and Palantir staff, is set to raise $ 18 million at a $ 100 million valuation. Check out the 14-slide pitch deck it used for its $ 2 million pre-seed" 3139: 1992:. On the other hand, on-line RSS-readers are available on almost any personal computer connected to the Internet. Users can download generated audio files to portable devices, e.g. with a help of 541: 885:. Leachim contained information regarding class curricular and certain biographical information about the students whom it was programmed to teach. It was tested in a fourth grade classroom in 821:, the desired target utterance is created by determining the best chain of candidate units from the database (unit selection). This process is typically achieved using a specially weighted 1935:

From 1971 to 1996, Votrax produced a number of commercial speech synthesizer components. A Votrax synthesizer was included in the first generation Kurzweil Reading Machine for the Blind.

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which included a Formant synthesis capability. Sequences of up to 512 individual vowel and consonant formants could be stored and replayed, allowing short vocal phrases to be synthesized.

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since the early 2000s has improved beyond the point of human's inability to tell a real human imaged with a real camera from a simulation of a human imaged with a simulation of a camera.

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reporter Joseph Cox published findings that he had recorded five minutes of himself talking and then used a tool developed by ElevenLabs to create voice deepfakes that defeated a bank's

208:. The front-end has two major tasks. First, it converts raw text containing symbols like numbers and abbreviations into the equivalent of written-out words. This process is often called 177:

The quality of a speech synthesizer is judged by its similarity to the human voice and by its ability to be understood clearly. An intelligible text-to-speech program allows people with

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Text-to-speech for disability and impaired communication aids have become widely available. Text-to-speech is also finding new applications; for example, speech synthesis combined with

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text-to-speech system. It featured a complete system of voice emulation for American English, with both male and female voices and "stress" indicator markers, made possible through the

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residual). Such pitch synchronous pitch modification techniques need a priori pitch marking of the synthesis speech database using techniques such as epoch extraction using dynamic

2112:) were capable of text-to-phoneme synthesis or reciting complete words and phrases (text-to-dictionary), using a very popular Speech Synthesizer peripheral. TI used a proprietary 2063:

Following the commercial failure of the hardware-based Intellivoice, gaming developers sparingly used software synthesis in later games. Earlier systems from Atari, such as the

84: 1182:: each time that speech is generated from the same string of text, the intonation of the speech will be slightly different. The application also supports manually altering the 765:

Unit selection synthesis uses large databases of recorded speech. During database creation, each recorded utterance is segmented into some or all of the following: individual

4961: 2351:. Work to personalize a synthetic voice to better match a person's personality or historical voice is becoming available. A noted application, of speech synthesis, was the 2007:. It can deliver TTS functionality to anyone (for reasons of accessibility, convenience, entertainment or information) with access to a web browser. The non-profit project 1426:). The simplest approach to text-to-phoneme conversion is the dictionary-based approach, where a large dictionary containing all the words of a language and their correct 585: 5452: 1776:

Standard Additions includes a say verb that allows a script to use any of the installed voices and to control the pitch, speaking rate and modulation of the spoken text.

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Prathosh, A. P.; Ramakrishnan, A. G.; Ananthapadmanabha, T. V. (December 2013). "Epoch extraction based on integrated linear prediction residual using plosion index".

86: 5368: 3118: 1575: 984:. Formant synthesizers are usually smaller programs than concatenative systems because they do not have a database of speech samples. They can therefore be used in 4595: 2485: 1633: 3528: 6441: 4575: 3309:. (2003). CMU ARCTIC databases for speech synthesis. CMU-LTI-03-177. Language Technologies Institute, School of Computer Science, Carnegie Mellon University. 1740:

into its systems which provided a fluid command set. More recently, Apple has added sample-based voices. Starting as a curiosity, the speech system of Apple

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in the late 1980s and merged with Apple Computer in 1997), the Trillium software was published under the GNU General Public License, with work continuing as

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Chadha, Anupama; Kumar, Vaibhav; Kashyap, Sonu; Gupta, Mayank (2021), Singh, Pradeep Kumar; Wierzchoń, Sławomir T.; Tanwar, Sudeep; Ganzha, Maria (eds.),

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Englert, Marina; Madazio, Glaucya; Gielow, Ingrid; Lucero, Jorge; Behlau, Mara (2016). "Perceptual error identification of human and synthesized voices".

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representations of their input texts, as processes for doing so are unreliable, poorly understood, and computationally ineffective. As a result, various

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that generates high-quality voices from an assortment of fictional characters from a variety of media sources was released. Initial characters included

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of the sentence, depending upon whether it is an affirmative, interrogative or exclamatory sentence. One of the techniques for pitch modification uses

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power are especially limited. Because formant-based systems have complete control of all aspects of the output speech, a wide variety of prosodies and

4428: 345:, Hungary, described in a 1791 paper. This machine added models of the tongue and lips, enabling it to produce consonants as well as vowels. In 1837, 4901: 4867: 3090: 1988:. On one hand, online RSS-narrators simplify information delivery by allowing users to listen to their favourite news sources and to convert them to 1871: 3201: 2795: 1804: 7195: 4730: 3581: 2008: 1765: 2378:

industries, able to generate narration and lines of dialogue according to user specifications. The application reached maturity in 2008, when NEC

1190:(a term coined by this project), a sentence or phrase that conveys the emotion of the take that serves as a guide for the model during inference. 5684: 2866: 1026:. Creating proper intonation for these projects was painstaking, and the results have yet to be matched by real-time text-to-speech interfaces. 5534: 1328:

ambiguous abbreviations, while others provide the same result in all cases, resulting in nonsensical (and sometimes comical) outputs, such as "

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and includes models of vocal frequency jitter and tremor, airflow noise and laryngeal asymmetries. The synthesizer has been used to mimic the

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Until recently, articulatory synthesis models have not been incorporated into commercial speech synthesis systems. A notable exception is the

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and the articulation processes occurring there. The first articulatory synthesizer regularly used for laboratory experiments was developed at

6579: 3995: 2322:, for example, includes tags related to speech recognition, dialogue management and touchtone dialing, in addition to text-to-speech markup. 742:. Each technology has strengths and weaknesses, and the intended uses of a synthesis system will typically determine which approach is used. 3617: 259:

information together make up the symbolic linguistic representation that is output by the front-end. The back-end—often referred to as the

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Jia, Ye; Zhang, Yu; Weiss, Ron J. (2018-06-12), "Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis",

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segmenting the waveforms sometimes result in audible glitches in the output. There are three main sub-types of concatenative synthesis.

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Examples of non-real-time but highly accurate intonation control in formant synthesis include the work done in the late 1970s for the

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Valle, Rafael (2020). "Mellotron: Multispeaker expressive voice synthesis by conditioning on rhythm, pitch and global style tokens".

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caused speech synthesizers to become cheaper and more accessible, more people would benefit from the use of text-to-speech programs.

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at MIT, and the Bell Labs system; the latter was one of the first multilingual language-independent systems, making extensive use of

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puts it to sleep. Despite the success of purely electronic speech synthesis, research into mechanical speech-synthesizers continues.

5510: 7159: 4704: 4496: 2945: 2388: 263:—then converts the symbolic linguistic representation into sound. In certain systems, this part includes the computation of the 4513:

Muralishankar, R.; Ramakrishnan, A. G.; Prathibha, P. (February 2004). "Modification of pitch using DCT in the source domain".

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to achieve text-to-speech synthesis, that can be made to sound almost like anybody from a speech sample of only 5 seconds.

1067:, where much of the original research was conducted. Following the demise of the various incarnations of NeXT (started by 7154: 5954: 5810: 5677: 4777: 2269: 2884:"A History of Realtime Digital Speech on Packet Networks: Part II of Linear Predictive Coding and the Internet Protocol" 7210: 6761: 6212: 4602: 3166: 1566: 1546: 1509:

regions of speech. In general, prosody remains a challenge for speech synthesizers, and is an active research topic.

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Since 2005, however, some researchers have started to evaluate speech synthesis systems using a common speech dataset.

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Muralishankar, R; Ramakrishnan, A.G.; Prathibha, P (2004). "Modification of Pitch using DCT in the Source Domain".

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allow users to create video content involving AI avatars, who are made to speak using text-to-speech technology.

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presented the work 'Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis', which

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Articulatory synthesis consists of computational techniques for synthesizing speech based on models of the human

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set to a "forced alignment" mode with some manual correction afterward, using visual representations such as the

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synthesis does not use human speech samples at runtime. Instead, the synthesized speech output is created using

364:, which automatically analyzed speech into its fundamental tones and resonances. From his work on the vocoder, 6751: 6496: 5887: 5705: 5670: 4798: 2348: 1371: 1142: 1052:, Tom Baer, and Paul Mermelstein. This synthesizer, known as ASY, was based on vocal tract models developed at 809:

of the units in the speech database is then created based on the segmentation and acoustic parameters like the

660:" programming technique to produce a synthesized speech waveform. Another early example, the arcade version of 493: 17: 5065:"Effect of Text-to-Speech and Human Reader on Listening Comprehension for Students with Learning Disabilities" 7200: 7020: 6741: 1531: 903: 462: 373: 42: 5237: 2382:

announced a web service that allows users to create phrases from the voices of characters from the Japanese

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cannot be reproduced by a simple word-concatenation system, which would require additional complexity to be

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and wider facial information from training material consisting of 2D videos with audio had been completed.

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can be output, conveying not just questions and statements, but a variety of emotions and tones of voice.

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2017 an audio driven digital look-alike of upper torso of Barack Obama was presented by researchers from

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portable calculator for the blind in 1976. Other devices had primarily educational purposes, such as the

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The MBROLA Project: Towards a set of high quality speech synthesizers of use for non commercial purposes

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Speech synthesis is a valuable computational aid for the analysis and assessment of speech disorders. A

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Speech synthesis systems use two basic approaches to determine the pronunciation of a word based on its

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produced a "speaking machine" based on von Kempelen's design, and in 1846, Joseph Faber exhibited the "

282:, some people tried to build machines to emulate human speech. Some early legends of the existence of " 5394: 3937: 3414: 3086: 2863: 1063:-based system originally developed and marketed by Trillium Sound Research, a spin-off company of the 7190: 6638: 6491: 6217: 5880: 5064: 3319: 2133: 1617: 1494: 938: 934: 874: 858: 829: 696: 38: 4020: 2593:

Rubin, P.; Baer, T.; Mermelstein, P. (1981). "An articulatory synthesizer for perceptual research".

2460: 7164: 7088: 6820: 6776: 6661: 6559: 6187: 6031: 5639: 5014: 3577: 3018:; Nebbia, Luciano (1 November 1995). "Interactive voice technology at work: The CSELT experience". 2533: 2503: 2335:

for people with visual impairment, but text-to-speech systems are now commonly used by people with

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system with similar aims at the 2018 NeurIPS conference, though the result is rather unconvincing.

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is a server-based package for voice synthesis and recognition. It is designed for network use with

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determine their pronunciations based on their spellings. This is similar to the "sounding out", or

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required and sometimes the output of speech synthesizer may result in the mistakes of tone sandhi.

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various automated methods to detect unnatural segments in unit-selection speech synthesis systems.

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was the first commercial all-software voice synthesis program. It was later used as the basis for

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in 1978. Fidelity released a speaking version of its electronic chess computer in 1979. The first

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as well as by pre-literate children. They are also frequently employed to aid those with severe

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2022 Wave Electronics and its Application in Information and Telecommunication Systems (WECONF)

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Proceedings of Second International Conference on Computing, Communications, and Cyber-Security

4193:"Anticipating and addressing the ethical implications of deepfakes in the context of elections" 3852: 3593: 3487: 2698:("Mechanism of the human speech with description of its speaking machine", J. B. Degen, Wien). 2513: 1769: 1536: 1313: 1035: 790: 703: 667: 639: 606: 513: 241: 225: 143: 6785: 6342: 6081: 5964: 5725: 5419: 4962:"An artificial-intelligence first: Voice-mimicking software reportedly used in a major theft" 3911: 3613: 3605: 3569: 2657:

Van Santen, J. (April 1994). "Assignment of segmental duration in text-to-speech synthesis".

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electronics featuring speech synthesis began emerging in the 1970s. One of the first was the

419:

The first computer-based speech-synthesis systems originated in the late 1950s. Noriko Umeda

338: 256: 229: 4626: 3258: 2817: 2315:. Although each of these was proposed as a standard, none of them have been widely adopted. 849:(sound-to-sound transitions) occurring in a language. The number of diphones depends on the 828:

Unit selection provides the greatest naturalness, because it applies only a small amount of

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researchers know of 3 cases where digital sound-alikes technology has been used for crime.

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which uses diphone-based synthesis, as well as more modern and better-sounding techniques.

1215:

For tonal languages, such as Chinese or Taiwanese language, there are different levels of

508:

during the 1970s. LPC was later the basis for early speech synthesizer chips, such as the

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is usually only pronounced when the following word has a vowel as its first letter (e.g.

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Proceedings of the 5th International Conference on Spoken Language Processing (ICSLP'98)

2764: 2606: 1733: 7128: 7000: 6865: 6628: 6611: 6469: 6357: 6347: 6258: 5820: 5762: 5730: 5453:"Arrested Succession Parody On YouTube Features 'Narration' By AI-Generated Ron Howard" 5369:"Sztuczna inteligencja czyta głosem Jarosława Kuźniara. Rewolucja w radiu i podcastach" 5192: 5147: 5102: 4910: 4876: 4557: 4488: 4280: 4220: 4167: 4139: 4110: 4071: 4053: 3831: 3678: 3333:

Automatic Detection of Unnatural Word-Level Segments in Unit-Selection Speech Synthesis

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Mechanismus der menschlichen Sprache nebst der Beschreibung seiner sprechenden Maschine

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van Santen, Jan P. H.; Sproat, Richard W.; Olive, Joseph P.; Hirschberg, Julia (1997).

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This increases the stress on the disinformation situation coupled with the facts that

2151: 2091: 1891: 1875: 1737: 1305:, like examining neighboring words and using statistics about frequency of occurrence. 1249: 1124: 1112: 1092: 953: 882: 794: 379: 346: 210: 182: 174:

and other human voice characteristics to create a completely "synthetic" voice output.

147: 4304:"AI gave Val Kilmer his voice back. But critics worry the technology could be misused" 3962: 2965: 2307:

in 2004. Older speech synthesis markup languages include Java Speech Markup Language (

2018:

through the W3C Audio Incubator Group with the involvement of The BBC and Google Inc.

566: 7133: 6845: 6653: 6564: 6322: 5856: 5805: 5720: 5485: 5427: 5315:"『Portal』のGLaDOSや『UNDERTALE』のサンズがテキストを読み上げてくれる。文章に込められた感情まで再現することを目指すサービス「15.ai」が話題に" 5196: 5182: 5151: 5137: 5133: 5106: 5094: 4802: 4799:

The Pediaphon – Speech Interface to the free Knowledge Encyclopedia for Mobile Phones

4708: 4683: 4369: 4311: 4284: 4270: 4224: 4212: 4171: 4157: 4098: 4075: 4045: 3970: 3912:"Generative AI comes for cinema dubbing: Audio AI startup ElevenLabs raises pre-seed" 3883:"『Portal』のGLaDOSや『UNDERTALE』のサンズがテキストを読み上げてくれる。文章に込められた感情まで再現することを目指すサービス「15.ai」が話題に" 3798: 3723: 3659: 3635: 3422: 3270: 3237: 3162: 3050: 3031: 2908: 2776: 2637: 2573: 2566: 2538: 2437: 2344: 2176: 1863: 1506: 1498: 1432: 1183: 1053: 1004: 766: 610: 489: 350: 279: 178: 162: 127: 4561: 4492: 4153: 4067: 3682: 3349: 2843: 2318:

Speech synthesis markup languages are distinguished from dialogue markup languages.

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was created in 2006 to provide a similar web-based TTS interface to the Knowledge.

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computer to synthesize speech, an event among the most prominent in the history of

387: 186: 5535:"AI-Generated Voice Firm Clamps Down After 4chan Makes Celebrity Voices for Abuse" 5178: 5171:

2021 IEEE EMBS International Conference on Biomedical and Health Informatics (BHI)

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Zhao, Yunxin; Song, Minguang; Yue, Yanghao; Kuruvilla-Dugdale, Mili (2021-07-27).

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The second operating system to feature advanced speech synthesis capabilities was

873:. or more recent techniques such as pitch modification in the source domain using 573: 7122: 7083: 7078: 6946: 6676: 6549: 6524: 6506: 6041: 5828: 4582: 4526: 4484: 4266: 4046:"Probing the phonetic and phonological knowledge of tones in Mandarin TTS models" 3719: 3532: 3400: 3122: 3104: 2993: 2870: 2415: 2409: 2370: 2352: 2292: 2255: 1857: 1294: 985: 926: 878: 671: 618: 556: 412: 291: 5314: 4393: 3882: 1760:) there was only one standard voice shipping with Mac OS X. Starting with 10.6 ( 267:(pitch contour, phoneme durations), which is then imposed on the output speech. 6830: 6810: 6534: 6388: 5166: 5121: 4929: 4679: 4131: 2198: 2187: 2095: 2079: 1981: 1753: 1729: 1245: 1236: 1229: 993: 497: 432: 392: 6419: 5656: 5648: 4553: 2197:

By 2019 the digital sound-alikes found their way to the hands of criminals as

161:. Systems differ in the size of the stored speech units; a system that stores 7184: 7093: 6905: 6885: 6666: 6408: 6398: 6317: 6061: 5911: 5489: 5431: 5098: 4373: 4315: 4216: 4208: 4136:

2020 IEEE International Conference on Multimedia & Expo Workshops (ICMEW)

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The process of normalizing text is rarely straightforward. Texts are full of

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Arık, Sercan Ö.; Chen, Jitong; Peng, Kainan; Ping, Wei; Zhou, Yanqi (2018),

4756:"How to configure and use Text-to-Speech in Windows XP and in Windows Vista" 4021:"ElevenLabs' Powerful New AI Tool Lets You Make a Full Audiobook in Minutes" 3996:"Voice-generating platform ElevenLabs raises $ 19M, launches detection tool" 3794: 2935:"The Distance Measure for Line Spectrum Pairs Applied to Speech Recognition" 2366: 7073: 6691: 6403: 6352: 6192: 6021: 5120:

Triandafilidi, Ioanis I.; Tatarnikova, T. M.; Poponin, A. S. (2022-05-30).

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Suwajanakorn, Supasorn; Seitz, Steven; Kemelmacher-Shlizerman, Ira (2017),

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TI will exit dedicated speech-synthesis chips, transfer products to Sensory

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Language Generation and Speech Synthesis in Dialogues for Language Learning

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Some models of Texas Instruments home computers produced in 1979 and 1981 (

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Sinewave synthesis is a technique for synthesizing speech by replacing the

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was one of the most famous people to use a speech computer to communicate.

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to embed complete spoken phrases into applications, primarily video games.

1996:

receiver, and listen to them while walking, jogging or commuting to work.

1809:

Example of speech synthesis with the included Say utility in Workbench 1.3

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developed the first general English text-to-speech system in 1968, at the

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in the 1960s and 1970s by Paul Mermelstein, Cecil Coker, and colleagues.

1041: 1019: 802: 621: 452: 318: 295: 283: 276: 171: 138:) system converts normal language text into speech; other systems render 6167: 5662: 5089: 577:

Fidelity Voice Chess Challenger (1979), the first talking chess computer

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Music technology (electronic and digital) § Vocal synthesis after 2010s

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The two primary technologies generating synthetic speech waveforms are

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speakers with controlled levels of roughness, breathiness and strain.

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DECtalk demo recording using the Perfect Paul and Uppity Ursula voices

244:. The process of assigning phonetic transcriptions to words is called 6501: 6268: 6112: 6091: 6086: 5940: 4671: 4539: 2772: 2614: 2472: 2464: 2123: 2102: 2046: 1829: 1749: 1745: 1741: 1647: 1302: 1298: 1108: 1072: 965: 886: 626: 505: 440: 369: 357: 342: 3511:

Proceedings ESCA-NATO Workshop and Applications of Speech Technology

2796:"Louis Gerstman, 61, a Specialist In Speech Disorders and Processes" 2751:

Klatt, D (1987). "Review of text-to-speech conversion for English".

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Popular systems offering speech synthesis as a built-in capability.

1345: 1091:, also called Statistical Parametric Synthesis. In this system, the 845:

Diphone synthesis uses a minimal speech database containing all the

6976: 6956: 6941: 6920: 6890: 6835: 6800: 6681: 6299: 6243: 6162: 6157: 6076: 6036: 5930: 5872: 5285:"ゲームキャラ音声読み上げソフト「15.ai」公開中。『Undertale』や『Portal』のキャラに好きなセリフを言ってもらえる" 4915: 4881: 4144: 4058: 3853:"ゲームキャラ音声読み上げソフト「15.ai」公開中。『Undertale』や『Portal』のキャラに好きなセリフを言ってもらえる" 3836: 2336: 2319: 2242: 2234: 2226: 2109: 1687: 1526: 1423: 1411: 1407: 1130: 973: 902:

unless the many variations are taken into account. For example, in

833: 798: 778: 774: 653: 594: 496:(NTT) in 1966. Further developments in LPC technology were made by 467: 396: 250: 158: 123: 5615:(Master of Music Music thesis). Florida International University. 4512: 3386: 3369:

T. Dutoit, V. Pagel, N. Pierret, F. Bataille, O. van der Vrecken.

3202:"Ann Syrdal, Who Helped Give Computers a Female Voice, Dies at 74" 2686:, Helsinki University of Technology, Retrieved on November 4, 2006 1505:

index applied on the integrated linear prediction residual of the

817:), duration, position in the syllable, and neighboring phones. At 200:

A text-to-speech system (or "engine") is composed of two parts: a

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which incorporated text-to-phonetics software based on work from

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incorporated the Texas Instruments TMS5220 speech synthesis chip.

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of a sentence is superimposed on these minimal units by means of

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have been established for the rendition of text as speech in an

1239:(also known as voice cloning or deepfake audio) is a product of 6479: 6474: 6383: 6253: 5980: 5926: 5643: 5119: 4858: 4596:"1400XL/1450XL Speech Handler External Reference Specification" 2627: 2468: 2397: 2360: 2250: 2172: 2145: 2137: 2034: 1917: 1606: 1282: 870: 786: 656:, for which the game's developer, Hiroshi Suzuki, developed a " 237: 233: 115: 4407: 4240:"Deepfake Audio Boom Exploits One Billion-Dollar Startup's AI" 3745: 3013: 2840:"Where "HAL" First Spoke (Bell Labs Speech Synthesis website)" 2214:

2D video forgery techniques were presented in 2016 that allow

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and Open Sesame), also had games utilizing software synthesis.

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The most important qualities of a speech synthesis system are

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and colleagues discovered acoustic cues for the perception of

313:

won the first prize in a competition announced by the Russian

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Remez, R.; Rubin, P.; Pisoni, D.; Carrell, T. (22 May 1981).

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Multilingual Text-to-Speech Synthesis: The Bell Labs Approach

2564:

Allen, Jonathan; Hunnicutt, M. Sharon; Klatt, Dennis (1987).

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to listen to written words on a home computer. Many computer

5164: 4989:. Proc. Computer Vision and Pattern Recognition (CVPR), IEEE 3629: 1813: 1301:

techniques are used to guess the proper way to disambiguate

6152: 4431:. University of Portsmouth. January 9, 2008. Archived from 2969: 2308: 1720:

MacinTalk 2 demo featuring the Mr. Hughes and Marvin voices

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to enable World English Spelling text-to-speech synthesis.

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Synthesized voices typically sounded male until 1990, when

5128:. St. Petersburg, Russian Federation: IEEE. pp. 1–5. 3705: 2148:

and others use speech synthesis for automobile navigation.

1824:, introduced in 1985. The voice synthesis was licensed by 1156:

Speech synthesis example using the HiFi-GAN neural vocoder

6966: 5652: 4939: 3963:"This Podcast Is Not Hosted by AI Voice Clones. We Swear" 2296: 2119: 2015: 1985: 189:

have included speech synthesizers since the early 1990s.

94:

A synthetic voice announcing an arriving train in Sweden.

5263:"Code Geass Speech Synthesizer Service Offered in Japan" 4731:"Accessibility Tutorials for Windows XP: Using Narrator" 3294:

Perfect synthesis for all of the people all of the time.

2711:

Mattingly, Ignatius G. (1974). Sebeok, Thomas A. (ed.).

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synthesizer, developed by Jorge C. Lucero et al. at the

1756:(10.4). During 10.4 (Tiger) and first releases of 10.5 ( 1690:

computers were sold with "stspeech.tos" on floppy disk.

4252: 4132:"Deepfake Detection: Current Challenges and Next Steps" 3765: 2713:"Speech synthesis for phonetic and phonological models" 1486: 1308:

Recently TTS systems have begun to use HMMs (discussed

1107:) of speech are modeled simultaneously by HMMs. Speech 368:

developed a keyboard-operated voice-synthesizer called

5420:"Generative AI Podcasts Are Here. Prepare to Be Bored" 5122:"Speech Synthesis System for People with Disabilities" 4447:"Smile – And The World Can Hear You, Even If You Hide" 4091:

Weaponised deep fakes: National security and democracy

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from SoftVoice, Inc., who also developed the original

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application that converts text to audible speech. The

976:

of artificial speech. This method is sometimes called

118:. A computer system used for this purpose is called a 5167:"Personalizing TTS Voices for Progressive Dysarthria" 4466:"The vocal communication of different kinds of smile" 4191:

Diakopoulos, Nicholas; Johnson, Deborah (June 2020).

3492:. World Future Society. 1978. pp. 359, 360, 361. 3346:"Pitch-Synchronous Overlap and Add (PSOLA) Synthesis" 3265:. Cambridge, UK: Cambridge University Press. p. 3146:. Vol. 11, no. 2. pp. 134-175 (160-3). 1671:

Arguably, the first speech system integrated into an

1410:, a process which is often called text-to-phoneme or 5649:

Simulated singing with the singing robot Pavarobotti

4362:"AI-Generated Voice Deepfakes Aren't Scary Good—Yet" 3447:"1960 - Rudy the Robot - Michael Freeman (American)" 2592: 2286: 1972:

and gadgets that can read messages directly from an

5559: 5063:Brunow, David A.; Cullen, Theresa A. (2021-07-03). 4089:Smith, Hannah; Mansted, Katherine (April 1, 2020). 3768:"Speech perception without traditional speech cues" 2563: 2169:

Conference on Neural Information Processing Systems

1999:A growing field in Internet based TTS is web-based 1878:. SAPI 4.0 was available as an optional add-on for 1087:HMM-based synthesis is a synthesis method based on 353:". In 1923, Paget resurrected Wheatstone's design. 5306: 5219:Journal of Rehabilitation Research and Development 4705:"Translator Library (Multilingual-speech version)" 4296: 4246: 4190: 3658:Lucero, J. C.; Schoentgen, J.; Behlau, M. (2013). 3505:, J.L. Gauvain, B. Prouts, C. Bouhier, R. Boesch. 3331:William Yang Wang and Kallirroi Georgila. (2011). 3161:. Vol. 1. SMG Szczepaniak. pp. 544–615. 2864:Anthropomorphic Talking Robot Waseda-Talker Series 2629: 2565: 1580:TI-99/4A speech demo using the built-in vocabulary 1462: 1293:Most text-to-speech (TTS) systems do not generate 590:Speech output from Fidelity Voice Chess Challenger 228:to each word, and divides and marks the text into 5395:"AI Can Clone Your Favorite Podcast Host's Voice" 4902:Advances in Neural Information Processing Systems 4868:Advances in Neural Information Processing Systems 4775: 4184: 3938:"AI Can Clone Your Favorite Podcast Host's Voice" 2988: 2986: 2440:using 15.ai and external voice control software. 1679:computers. These used the Votrax SC01 chip and a 551:Dominant systems in the 1980s and 1990s were the 7182: 6652: 5560:"Usage of text-to-speech in AI video generation" 5010:Synthesizing Obama: Learning Lip Sync from Audio 4894: 3874: 3140:"The Replay Years: Reflections from Eddie Adlum" 1616:Voice Synthesis module in 1982. It included the 1552: 1272: 1136: 1133:(main bands of energy) with pure tone whistles. 1111:are generated from HMMs themselves based on the 411:Computer and speech synthesizer housing used by 372:(Voice Demonstrator), which he exhibited at the 6449: 5238:"Speech Synthesis Software for Anime Announced" 2432:allows for interaction with mobile devices via 2014:Other work is being done in the context of the 157:pieces of recorded speech that are stored in a 4778:"An introduction to Text-To-Speech in Android" 3660:"Physics-based synthesis of disordered voices" 3507:Generation and Synthesis of Broadcast Messages 3159:The Untold History of Japanese Game Developers 2983: 2726:. Mouton, The Hague: 2451–2487. Archived from 1944:are available through third-party publishers. 1521:A speech synthesis kit produced by Bell System 6435: 5888: 5678: 4864: 4748: 2932: 1931:Votrax Type 'N Talk speech synthesizer (1980) 1335: 5062: 4930:"Fake voices 'help cyber-crooks steal cash'" 4542:IEEE Trans. Audio Speech Language Processing 4088: 3618:Escape from the Planet of the Robot Monsters 3193: 3187:Smithsonian Speech Synthesis History Project 2933:Zheng, F.; Song, Z.; Li, L.; Yu, W. (1998). 2753:Journal of the Acoustical Society of America 2595:Journal of the Acoustical Society of America 2436:interfaces. Some users have also created AI 1744:has evolved into a fully supported program, 1320:is frequently difficult in these languages. 892: 565: 5026: 3156: 3095:: "Talking electronic game", April 27, 1982 2684:History and Development of Speech Synthesis 2049:which uses articulatory synthesis from the 2003:, e.g. 'Browsealoud' from a UK company and 1874:components to support speech synthesis and 1752:was for the first time featured in 2005 in 1724:The first speech system integrated into an 1585:with speech during this promotion included 1374:. Unsourced material may be challenged and 1332:" being rendered as "Ulysses South Grant". 760: 709: 329:notation: , , , and ). There followed the 23: 6442: 6428: 5895: 5881: 5685: 5671: 5478:"Can A.I. Be Funny? This Troupe Thinks So" 5276: 4670: 4627:"It Sure Is Great To Get Out Of That Bag!" 3823: 2996:. IEEE Global History Network. 20 May 2009 2656: 2154:produced a music synthesizer in 1999, the 2037:which supports a broad range of languages. 1956:added support for speech synthesis (TTS). 745: 470:computer sings the same song as astronaut 24: 5692: 5620: 5312: 5088: 4914: 4897:"Neural Voice Cloning with a Few Samples" 4888: 4880: 4143: 4057: 3880: 3844: 3835: 3554:Star Trek: Strategic Operations Simulator 3322:, masters thesis, Section 5.6 on page 54. 2902: 2710: 1938: 1394:Learn how and when to remove this message 1029: 617:to feature speech synthesis was the 1980 5392: 5282: 4953: 4723: 3935: 3850: 3224: 3199: 2365: 1984:. Some specialized software can narrate 1921: 1799: 1710: 1697: 1657: 1628: 1570: 1516: 1450: 1309: 1146: 972:levels are varied over time to create a 580: 572: 537: 519:In 1975, Fumitada Itakura developed the 406: 255:conversion. Phonetic transcriptions and 191: 32:This is an accepted version of this page 7196:Applications of artificial intelligence 5000: 4978: 4922: 4733:. Microsoft. 2011-01-29. Archived from 4463: 4334: 4203:(7) (published 2020-06-05): 2072–2098. 3993: 3960: 3742:"The HMM-based Speech Synthesis System" 2960: 2958: 2793: 2677: 2389:Code Geass: Lelouch of the Rebellion R2 2162: 702:Kurzweil predicted in 2005 that as the 14: 7183: 5475: 5173:. Athens, Greece: IEEE. pp. 1–4. 4702: 4237: 3256: 3044: 2568:From Text to Speech: The MITalk system 2353:Kurzweil Reading Machine for the Blind 2299:-compliant format. The most recent is 2110:Texas Instruments TI-99/4 and TI-99/4A 1082: 443:. Kelly's voice recorder synthesizer ( 114:is the artificial production of human 7216:History of human–computer interaction 6423: 5876: 5666: 5657:how the robot synthesized the singing 5608: 5336: 4984: 4095:Australian Strategic Policy Institute 3829: 3701: 3699: 3653: 3651: 3630:John Holmes and Wendy Holmes (2001). 3137: 2750: 2392:. 15.ai has been frequently used for 2359:and a black-box synthesizer built by 1512: 1481:by Amy Drahota and colleagues at the 1118: 555:system, based largely on the work of 484:, began development with the work of 402: 315:Imperial Academy of Sciences and Arts 153:Synthesized speech can be created by 59:Artificial production of human speech 6901:Simple Knowledge Organization System 5902: 5527: 5508: 5386: 4959: 4619: 4335:Etienne, Vanessa (August 19, 2021). 3744:. Hts.sp.nitech.ac.j. Archived from 3586:Indiana Jones and the Temple of Doom 2955: 2881: 2544:Text to speech in digital television 2478: 1851: 1675:was the circa 1983 unreleased Atari 1560: 1422:to describe distinctive sounds in a 1372:adding citations to reliable sources 1339: 1160:Deep learning speech synthesis uses 944: 840: 146:into speech. The reverse process is 5502: 5313:Yoshiyuki, Furushima (2021-01-18). 4429:"Smile -and the world can hear you" 4129: 4043: 3987: 3929: 3881:Yoshiyuki, Furushima (2021-01-18). 3014:Billi, Roberto; Canavesio, Franco; 2403:My Little Pony: Friendship Is Magic 2270:My Little Pony: Friendship Is Magic 2126:included VoiceType, a precursor to 1748:, for people with vision problems. 451:", with musical accompaniment from 140:symbolic linguistic representations 56: 6213:Texas Instruments LPC Speech Chips 5612:Vocal Synthesis and Deep Listening 5417: 5393:Ashworth, Boone (April 12, 2023). 5265:. Animenewsnetwork.com. 2008-09-09 5032: 4703:Devitt, Francesco (30 June 1995). 4359: 4238:Murphy, Margi (20 February 2024). 3936:Ashworth, Boone (April 12, 2023). 3696: 3648: 3476:. New York Media, LLC. 1979-07-30. 3116:Gaming's most important evolutions 1812: 1567:Texas Instruments LPC Speech Chips 1547:Texas Instruments LPC Speech Chips 1222: 510:Texas Instruments LPC Speech Chips 399:segments (consonants and vowels). 335:acoustic-mechanical speech machine 66: 57: 7227: 6916:Thesaurus (information retrieval) 5633: 5450: 4780:. Android-developers.blogspot.com 2794:Lambert, Bruce (March 21, 1992). 2509:Comparison of speech synthesizers 2287:Speech synthesis markup languages 1964:Currently, there are a number of 1178:model used by the application is 321:that could produce the five long 317:for models he built of the human 6290:Speech Synthesis Markup Language 5951:Festival Speech Synthesis System 5602: 5577: 5552: 5469: 5444: 5411: 5361: 5134:10.1109/WECONF55058.2022.9803600 4843:. Mindspring.com. Archived from 4776:Jean-Michel Trivi (2009-09-23). 4018: 3632:Speech Synthesis and Recognition 3415:"Education: Marvel of The Bronx" 3183:"A Short History of Computalker" 2951:from the original on 2022-10-09. 2922:from the original on 2022-10-09. 2484:This section is an excerpt from 2301:Speech Synthesis Markup Language 2041:Festival Speech Synthesis System 2030:systems are available, such as: 1435:, approach to learning reading. 1344: 1228:This section is an excerpt from 670:produced the first multi-player 196:Overview of a typical TTS system 102:Problems playing this file? See 82: 6052:Microsoft text-to-speech voices 5609:Bruno, Chelsea A (2014-03-25). 5325:from the original on 2021-01-18 5295:from the original on 2021-01-19 5255: 5230: 5203: 5158: 5113: 5056: 4833: 4812: 4791: 4769: 4696: 4676:Amiga Hardware Reference Manual 4664: 4640: 4588: 4533: 4506: 4457: 4439: 4421: 4400: 4386: 4353: 4328: 4231: 4154:10.1109/icmew46912.2020.9105991 4123: 4082: 4068:10.21437/speechprosody.2020-190 4037: 4012: 3954: 3904: 3893:from the original on 2021-01-18 3863:from the original on 2021-01-19 3759: 3734: 3623: 3558: 3538: 3516: 3496: 3480: 3464: 3439: 3407: 3380: 3363: 3338: 3325: 3312: 3299: 3283: 3250: 3218: 3175: 3150: 3131: 3109: 3098: 3078: 3069: 3063: 3038: 3007: 2994:"Fumitada Itakura Oral History" 2926: 2875: 2857: 2832: 2806: 2325: 1463:Prosodics and emotional content 327:International Phonetic Alphabet 311:Christian Gottlieb Kratzenstein 6497:Natural language understanding 5585:"AI Text to speech for videos" 5035:"Voice Cloning for the Masses" 4396:. World Wide Web Organization. 3138:Adlum, Eddie (November 1985). 2787: 2744: 2704: 2689: 2659:Computer Speech & Language 2650: 2621: 2586: 2572:. Cambridge University Press. 2557: 2349:voice output communication aid 2021: 1667:Atari ST speech synthesis demo 1143:Deep learning speech synthesis 1103:(voice source), and duration ( 494:Nippon Telegraph and Telephone 13: 1: 7021:Optical character recognition 5283:Kurosawa, Yuki (2021-01-19). 5179:10.1109/BHI50953.2021.9508522 5081:10.1080/07380569.2021.1953362 4115:: CS1 maint: date and year ( 3851:Kurosawa, Yuki (2021-01-19). 3675:10.21437/Interspeech.2013-161 2720:Current Trends in Linguistics 2550: 2136:Navigation units produced by 1728:that shipped in quantity was 1553:Hardware and software systems 1532:General Instrument SP0256-AL2 1273:Text normalization challenges 1267: 1137:Deep learning-based synthesis 427:in Japan. In 1961, physicist 275:Long before the invention of 224:. The front-end then assigns 6714:Multi-document summarization 4960:Drew, Harwell (2019-09-04). 4527:10.1016/j.specom.2003.05.001 4485:10.1016/j.specom.2007.10.001 4267:10.1007/978-981-16-0733-2_39 3994:Wiggers, Kyle (2023-06-20). 3720:10.1016/j.jvoice.2015.07.017 3401:10.1016/j.specom.2003.05.001 3032:10.1016/0167-6393(95)00030-R 2891:Found. Trends Signal Process 2814:"Arthur C. Clarke Biography" 2632:Progress in Speech Synthesis 2347:usually through a dedicated 1469:Emotional speech recognition 958:physical modelling synthesis 666:, also dates from 1980. The 652:), released in 1980 for the 122:, and can be implemented in 7: 7044:Latent Dirichlet allocation 7016:Natural language generation 6881:Machine-readable dictionary 6876:Linguistic Linked Open Data 6451:Natural language processing 5476:Fadulu, Lola (2023-07-06). 5041:. The Batch. Archived from 3045:Sproat, Richard W. (1997). 2842:. Bell Labs. Archived from 2519:Orca (assistive technology) 2496: 2463:, simulates the physics of 2434:natural language processing 2171:(NeurIPS) researchers from 1959: 1539:DT1050 Digitalker (Mozer – 1196:is primarily known for its 561:natural language processing 425:Electrotechnical Laboratory 10: 7232: 6796:Explicit semantic analysis 6545:Deep linguistic processing 5651:or a description from the 5375:(in Polish). April 9, 2023 3157:Szczepaniak, John (2014). 2483: 1947: 1915: 1855: 1795: 1564: 1466: 1336:Text-to-phoneme challenges 1227: 1186:of a generated line using 1140: 1122: 1033: 749: 699:, created a female voice. 697:AT&T Bell Laboratories 642:with speech synthesis was 374:1939 New York World's Fair 270: 7211:Computational linguistics 7147: 7102: 7057: 7029: 6989: 6934: 6856: 6844: 6775: 6732: 6704: 6639:Word-sense disambiguation 6515: 6492:Computational linguistics 6457: 6366: 6308: 6282: 6231: 6218:General Instrument SP0256 6180: 6105: 6014: 6003: 5973: 5919: 5910: 5842: 5819: 5781: 5744: 5701: 5033:Ng, Andrew (2020-04-01). 4682:Publishing Company, Inc. 4554:10.1109/TASL.2013.2273717 2966:"List of IEEE Milestones" 2057: 1911: 1779: 1612:game console offered the 1600: 1495:discrete cosine transform 1188:emotional contextualizers 1011:, and in the early 1980s 893:Domain-specific synthesis 875:discrete cosine transform 859:digital signal processing 830:digital signal processing 7165:Natural Language Toolkit 7089:Pronunciation assessment 6991:Automatic identification 6821:Latent semantic analysis 6777:Distributional semantics 6662:Compound-term processing 6560:Named-entity recognition 6032:Software Automatic Mouth 5069:Computers in the Schools 5015:University of Washington 4652:Amazon Web Services, Inc 4209:10.1177/1461444820925811 4044:Zhu, Jian (2020-05-25). 3261:Text-to-speech synthesis 2882:Gray, Robert M. (2010). 2534:Speech-generating device 2504:Chinese speech synthesis 2231:University of Washington 2051:Free Software Foundation 1866:desktop systems can use 1693: 1653: 1644:Software Automatic Mouth 1638:A demo of SAM on the C64 1483:University of Portsmouth 1414:-to-phoneme conversion ( 906:dialects of English the 863:linear predictive coding 761:Unit selection synthesis 710:Synthesizer technologies 599:Telesensory Systems Inc. 478:Linear predictive coding 39:latest accepted revision 7069:Automated essay scoring 7039:Document classification 6706:Automatic summarization 6379:Concatenative synthesis 6264:Microsoft Speech Server 6133:NIAONiao Virtual Singer 5622:10.25148/etd.fi14040802 4758:. Microsoft. 2007-05-07 4255:"Deepfake: An Overview" 4197:New Media & Society 4052:. ISCA: ISCA: 930–934. 3795:10.1126/science.7233191 3582:The Empire Strikes Back 3296:IEEE TTS Workshop 2002. 3230:The Singularity is Near 3200:CadeMetz (2020-08-20). 2529:Silent speech interface 2303:(SSML), which became a 2245:web application called 1898:Microsoft Speech Server 1826:Commodore International 1642:Also released in 1982, 1477:A study in the journal 1241:artificial intelligence 1022:arcade games using the 956:and an acoustic model ( 881:, that was invented by 752:Concatenative synthesis 746:Concatenation synthesis 733:concatenative synthesis 674:using voice synthesis, 226:phonetic transcriptions 144:phonetic transcriptions 6926:Universal Dependencies 6619:Terminology extraction 6602:Semantic decomposition 6597:Semantic role labeling 6587:Part-of-speech tagging 6555:Information extraction 6540:Coreference resolution 6530:Collocation extraction 6374:Articulatory synthesis 6328:Franklin Seaney Cooper 4985:Thies, Justus (2016). 4674:; et al. (1991). 3714:(5): 639.e17–639.e23. 3105:Voice Chess Challenger 2671:10.1006/csla.1994.1005 2514:List of screen readers 2461:University of Brasília 2374: 2186:Also researchers from 1939:Text-to-speech systems 1932: 1817: 1810: 1721: 1708: 1668: 1639: 1624: 1581: 1537:National Semiconductor 1522: 1497:in the source domain ( 1157: 1036:Articulatory synthesis 1030:Articulatory synthesis 960:). Parameters such as 704:cost-performance ratio 668:Milton Bradley Company 640:personal computer game 591: 578: 570: 548: 447:) recreated the song " 416: 382:and his colleagues at 380:Dr. Franklin S. Cooper 197: 78:Automatic announcement 71: 6687:Sentence segmentation 6343:Wolfgang von Kempelen 6123:CeVIO Creative Studio 6082:CeVIO Creative Studio 5965:Automatik Text Reader 5811:Karplus–Strong string 3634:(2nd ed.). CRC. 3257:Taylor, Paul (2009). 3075:Gevaryahu, Jonathan, 2422:SpongeBob SquarePants 2369: 2222:in existing 2D video. 2209:Human image synthesis 2098:, and the Bebook Neo. 1976:and web pages from a 1930: 1816: 1808: 1790:Software as a Service 1719: 1706: 1666: 1637: 1579: 1520: 1473:Prosody (linguistics) 1451:Evaluation challenges 1155: 1101:fundamental frequency 1065:University of Calgary 1018:machines and in many 978:rules-based synthesis 962:fundamental frequency 811:fundamental frequency 607:Speak & Spell toy 589: 576: 569: 546: 463:2001: A Space Odyssey 410: 339:Wolfgang von Kempelen 195: 70: 7201:Assistive technology 7139:Voice user interface 6850:datasets and corpora 6791:Document-term matrix 6644:Word-sense induction 6338:Haskins Laboratories 6047:Microsoft Speech API 5862:Software synthesizer 5706:Frequency modulation 4515:Speech Communication 4473:Speech Communication 4464:Drahota, A. (2008). 4408:"Blizzard Challenge" 3389:Speech Communication 3352:on February 22, 2007 3020:Speech Communication 2820:on December 11, 1997 2357:Haskins Laboratories 2341:reading disabilities 2181:speaker verification 2163:Digital sound-alikes 2028:open-source software 2001:assistive technology 1792:in AWS (from 2017). 1681:finite state machine 1479:Speech Communication 1444:phonemic orthography 1418:is the term used by 1368:improve this section 1262:voice-authentication 1162:deep neural networks 1089:hidden Markov models 1048:in the mid-1970s by 1046:Haskins Laboratories 680:, in the same year. 502:Manfred R. Schroeder 429:John Larry Kelly, Jr 384:Haskins Laboratories 183:reading disabilities 7119:Interactive fiction 7049:Pachinko allocation 7006:Speech segmentation 6962:Google Ngram Viewer 6734:Machine translation 6724:Text simplification 6719:Sentence extraction 6607:Semantic similarity 5844:Digital synthesizer 4711:on 26 February 2012 4130:Lyu, Siwei (2020). 4050:Speech Prosody 2020 3787:1981Sci...212..947R 3614:Vindicators Part II 3525:Music and Computers 3522:Dartmouth College: 3016:Ciaramella, Alberto 2765:1987ASAJ...82..737K 2607:1981ASAJ...70..321R 2067:(Baseball) and the 1172:multi-speaker model 1083:HMM-based synthesis 887:the Bronx, New York 861:techniques such as 630:(known in Japan as 521:line spectral pairs 492:and Shuzo Saito of 29:Page version status 7129:Question answering 7001:Speech recognition 6866:Corpus linguistics 6846:Language resources 6629:Textual entailment 6612:Sentiment analysis 6348:Ignatius Mattingly 5821:Analog synthesizer 5783:Physical modelling 5541:. January 30, 2023 5509:Kanetkar, Riddhi. 5482:The New York Times 5242:Anime News Network 4797:Andreas Bischoff, 4581:2012-05-28 at the 4394:"Speech synthesis" 4360:Newman, Lily Hay. 4097:. pp. 11–13. 3918:. January 23, 2023 3574:Return of the Jedi 3531:2011-06-08 at the 3206:The New York Times 3121:2011-06-15 at the 2904:10.1561/2000000036 2869:2016-03-04 at the 2800:The New York Times 2438:virtual assistants 2430:speech recognition 2375: 2305:W3C recommendation 2220:facial expressions 2218:counterfeiting of 2177:transfers learning 2092:PocketBook eReader 1933: 1876:speech recognition 1818: 1811: 1770:command-line based 1738:speech recognition 1722: 1709: 1669: 1640: 1582: 1523: 1513:Dedicated hardware 1250:speech translation 1158: 1125:Sinewave synthesis 1119:Sinewave synthesis 1113:maximum likelihood 1093:frequency spectrum 954:additive synthesis 883:Michael J. Freeman 632:Speak & Rescue 592: 579: 571: 549: 455:. Coincidentally, 431:and his colleague 417: 403:Electronic devices 347:Charles Wheatstone 211:text normalization 198: 179:visual impairments 148:speech recognition 120:speech synthesizer 72: 35: 7206:Auditory displays 7178: 7177: 7134:Virtual assistant 7059:Computer-assisted 6985: 6984: 6742:Computer-assisted 6700: 6699: 6692:Word segmentation 6654:Text segmentation 6592:Semantic analysis 6580:Syntactic parsing 6565:Ontology learning 6417: 6416: 6323:Catherine Browman 6176: 6175: 5999: 5998: 5986:Lyricos / Flinger 5870: 5869: 5857:Scanned synthesis 5796:Digital waveguide 5711:Linear arithmetic 5188:978-1-6654-0358-0 5143:978-1-6654-7083-4 4689:978-0-201-56776-2 4585:." June 14, 2001. 4548:(12): 2471–2480. 4276:978-981-16-0732-5 4163:978-1-7281-1485-9 3781:(4497): 947–949. 3641:978-0-7484-0856-6 3564:Examples include 3544:Examples include 3513:, September 1993. 3473:New York Magazine 3451:cyberneticzoo.com 3375:ICSLP Proceedings 3335:, IEEE ASRU 2011. 3305:John Kominek and 3243:978-0-14-303788-0 3226:Kurzweil, Raymond 3056:978-0-7923-8027-6 2643:978-0-387-94701-3 2579:978-0-521-30641-6 2539:Speech processing 2479:Singing synthesis 2345:speech impairment 2241:In March 2020, a 1928: 1852:Microsoft Windows 1806: 1717: 1704: 1664: 1635: 1577: 1561:Texas Instruments 1499:linear prediction 1442:Languages with a 1433:synthetic phonics 1404: 1403: 1396: 1153: 1054:Bell Laboratories 1024:TMS5220 LPC Chips 1009:Speak & Spell 1005:Texas Instruments 945:Formant synthesis 939:context-sensitive 841:Diphone synthesis 795:speech recognizer 611:Texas Instruments 587: 544: 514:Speak & Spell 490:Nagoya University 480:(LPC), a form of 294:(1198–1280), and 280:signal processing 187:operating systems 89: 47:17 September 2024 26: 16:(Redirected from 7223: 7191:Speech synthesis 7155:Formal semantics 7104:Natural language 7011:Speech synthesis 6993:and data capture 6896:Semantic network 6871:Lexical resource 6854: 6853: 6672:Lexical analysis 6650: 6649: 6575:Semantic parsing 6444: 6437: 6430: 6421: 6420: 6259:Windows Narrator 6198:Pattern playback 6148:Symphonic Choirs 6012: 6011: 5917: 5916: 5904:Speech synthesis 5897: 5890: 5883: 5874: 5873: 5791:Banded waveguide 5716:Phase distortion 5687: 5680: 5673: 5664: 5663: 5640:Speech synthesis 5627: 5626: 5624: 5606: 5600: 5599: 5597: 5595: 5581: 5575: 5574: 5572: 5570: 5556: 5550: 5549: 5547: 5546: 5531: 5525: 5524: 5522: 5521: 5515:Business Insider 5506: 5500: 5499: 5497: 5496: 5473: 5467: 5466: 5464: 5463: 5448: 5442: 5441: 5439: 5438: 5415: 5409: 5408: 5406: 5405: 5390: 5384: 5383: 5381: 5380: 5365: 5359: 5358: 5356: 5355: 5340: 5334: 5333: 5331: 5330: 5319:Denfaminicogamer 5310: 5304: 5303: 5301: 5300: 5280: 5274: 5273: 5271: 5270: 5259: 5253: 5252: 5250: 5249: 5234: 5228: 5227: 5215: 5207: 5201: 5200: 5162: 5156: 5155: 5117: 5111: 5110: 5092: 5060: 5054: 5053: 5051: 5050: 5030: 5024: 5023: 5022: 5021: 5004: 4998: 4997: 4995: 4994: 4982: 4976: 4975: 4973: 4972: 4957: 4951: 4950: 4948: 4947: 4926: 4920: 4919: 4918: 4892: 4886: 4885: 4884: 4862: 4856: 4855: 4853: 4852: 4837: 4831: 4830: 4828: 4827: 4816: 4810: 4795: 4789: 4788: 4786: 4785: 4773: 4767: 4766: 4764: 4763: 4752: 4746: 4745: 4743: 4742: 4737:on June 21, 2003 4727: 4721: 4720: 4718: 4716: 4707:. 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Archived from 3772: 3763: 3757: 3756: 3754: 3753: 3738: 3732: 3731: 3708:Journal of Voice 3703: 3694: 3693: 3691: 3689: 3667:Interspeech 2013 3664: 3655: 3646: 3645: 3627: 3621: 3562: 3556: 3542: 3536: 3520: 3514: 3500: 3494: 3493: 3484: 3478: 3477: 3468: 3462: 3461: 3459: 3458: 3443: 3437: 3436: 3434: 3433: 3411: 3405: 3404: 3384: 3378: 3367: 3361: 3360: 3358: 3357: 3348:. Archived from 3342: 3336: 3329: 3323: 3316: 3310: 3303: 3297: 3287: 3281: 3280: 3264: 3254: 3248: 3247: 3222: 3216: 3215: 3213: 3212: 3197: 3191: 3190: 3179: 3173: 3172: 3154: 3148: 3147: 3135: 3129: 3113: 3107: 3102: 3096: 3094: 3093: 3089: 3084:Breslow, et al. 3082: 3076: 3073: 3067: 3061: 3060: 3042: 3036: 3035: 3011: 3005: 3004: 3002: 3001: 2990: 2981: 2980: 2978: 2976: 2962: 2953: 2952: 2950: 2939: 2930: 2924: 2923: 2921: 2906: 2888: 2879: 2873: 2861: 2855: 2854: 2852: 2851: 2836: 2830: 2829: 2827: 2825: 2816:. 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Clarke 388:Pattern playback 286:" involved Pope 112:Speech synthesis 91: 90: 69: 21: 7231: 7230: 7226: 7225: 7224: 7222: 7221: 7220: 7181: 7180: 7179: 7174: 7143: 7123:Syntax guessing 7105: 7098: 7084:Predictive text 7079:Grammar checker 7060: 7053: 7025: 6992: 6981: 6947:Bank of English 6930: 6858: 6849: 6840: 6771: 6728: 6696: 6648: 6550:Distant reading 6525:Argument mining 6511: 6507:Text processing 6453: 6448: 6418: 6413: 6362: 6310: 6304: 6278: 6227: 6172: 6101: 6042:Microsoft Agent 6006: 5995: 5969: 5906: 5901: 5871: 5866: 5852:Analog modeling 5838: 5829:Graphical sound 5815: 5777: 5740: 5697: 5694:Sound synthesis 5691: 5636: 5631: 5630: 5607: 5603: 5593: 5591: 5583: 5582: 5578: 5568: 5566: 5558: 5557: 5553: 5544: 5542: 5533: 5532: 5528: 5519: 5517: 5507: 5503: 5494: 5492: 5474: 5470: 5461: 5459: 5449: 5445: 5436: 5434: 5416: 5412: 5403: 5401: 5391: 5387: 5378: 5376: 5367: 5366: 5362: 5353: 5351: 5342: 5341: 5337: 5328: 5326: 5311: 5307: 5298: 5296: 5281: 5277: 5268: 5266: 5261: 5260: 5256: 5247: 5245: 5236: 5235: 5231: 5213: 5209: 5208: 5204: 5189: 5163: 5159: 5144: 5118: 5114: 5061: 5057: 5048: 5046: 5039:deeplearning.ai 5031: 5027: 5019: 5017: 5005: 5001: 4992: 4990: 4983: 4979: 4970: 4968: 4966:Washington Post 4958: 4954: 4945: 4943: 4928: 4927: 4923: 4893: 4889: 4863: 4859: 4850: 4848: 4839: 4838: 4834: 4825: 4823: 4818: 4817: 4813: 4796: 4792: 4783: 4781: 4774: 4770: 4761: 4759: 4754: 4753: 4749: 4740: 4738: 4729: 4728: 4724: 4714: 4712: 4701: 4697: 4690: 4669: 4665: 4656: 4654: 4646: 4645: 4641: 4632: 4630: 4625: 4624: 4620: 4611: 4609: 4605: 4598: 4594: 4593: 4589: 4583:Wayback Machine 4573: 4569: 4538: 4534: 4511: 4507: 4499: 4468: 4462: 4458: 4453:. January 2008. 4445: 4444: 4440: 4427: 4426: 4422: 4413: 4411: 4406: 4405: 4401: 4392: 4391: 4387: 4378: 4376: 4358: 4354: 4345: 4343: 4333: 4329: 4320: 4318: 4308:Washington Post 4302: 4301: 4297: 4289: 4287: 4277: 4251: 4247: 4236: 4232: 4189: 4185: 4176: 4174: 4164: 4128: 4124: 4108: 4107: 4087: 4083: 4042: 4038: 4029: 4027: 4017: 4013: 4004: 4002: 3992: 3988: 3979: 3977: 3959: 3955: 3946: 3944: 3934: 3930: 3921: 3919: 3910: 3909: 3905: 3896: 3894: 3879: 3875: 3866: 3864: 3849: 3845: 3828: 3824: 3815: 3813: 3809: 3770: 3764: 3760: 3751: 3749: 3740: 3739: 3735: 3704: 3697: 3687: 3685: 3662: 3656: 3649: 3642: 3628: 3624: 3563: 3559: 3543: 3539: 3533:Wayback Machine 3521: 3517: 3501: 3497: 3486: 3485: 3481: 3470: 3469: 3465: 3456: 3454: 3445: 3444: 3440: 3431: 3429: 3413: 3412: 3408: 3385: 3381: 3368: 3364: 3355: 3353: 3344: 3343: 3339: 3330: 3326: 3317: 3313: 3304: 3300: 3288: 3284: 3277: 3255: 3251: 3244: 3223: 3219: 3210: 3208: 3198: 3194: 3181: 3180: 3176: 3169: 3155: 3151: 3136: 3132: 3123:Wayback Machine 3114: 3110: 3103: 3099: 3091: 3085: 3083: 3079: 3074: 3070: 3064: 3057: 3043: 3039: 3012: 3008: 2999: 2997: 2992: 2991: 2984: 2974: 2972: 2964: 2963: 2956: 2948: 2937: 2931: 2927: 2919: 2886: 2880: 2876: 2871:Wayback Machine 2862: 2858: 2849: 2847: 2838: 2837: 2833: 2823: 2821: 2812: 2811: 2807: 2792: 2788: 2749: 2745: 2736: 2734: 2730: 2715: 2709: 2705: 2699: 2694: 2690: 2682: 2678: 2655: 2651: 2644: 2626: 2622: 2591: 2587: 2580: 2562: 2558: 2553: 2548: 2499: 2494: 2493: 2489: 2481: 2410:Team Fortress 2 2371:Stephen Hawking 2328: 2289: 2165: 2060: 2024: 1962: 1952:Version 1.6 of 1950: 1941: 1922: 1920: 1914: 1860: 1858:Microsoft Agent 1854: 1800: 1798: 1782: 1711: 1698: 1696: 1658: 1656: 1629: 1627: 1618:SP0256 Narrator 1603: 1571: 1569: 1563: 1555: 1515: 1475: 1465: 1453: 1400: 1389: 1383: 1380: 1365: 1349: 1338: 1314:parts of speech 1312:) to generate " 1275: 1270: 1254: 1253: 1233: 1225: 1223:Audio deepfakes 1147: 1145: 1139: 1127: 1121: 1085: 1038: 1032: 947: 925:). Likewise in 921:is realized as 895: 843: 773:, half-phones, 763: 754: 748: 721:intelligibility 712: 672:electronic game 636:Sun Electronics 581: 538: 413:Stephen Hawking 405: 292:Albertus Magnus 273: 246:text-to-phoneme 109: 108: 100: 98: 97: 96: 95: 92: 83: 80: 73: 67: 60: 55: 54: 53: 52: 51: 50: 34: 22: 15: 12: 11: 5: 7229: 7219: 7218: 7213: 7208: 7203: 7198: 7193: 7176: 7175: 7173: 7172: 7167: 7162: 7157: 7151: 7149: 7145: 7144: 7142: 7141: 7136: 7131: 7126: 7116: 7110: 7108: 7106:user interface 7100: 7099: 7097: 7096: 7091: 7086: 7081: 7076: 7071: 7065: 7063: 7055: 7054: 7052: 7051: 7046: 7041: 7035: 7033: 7027: 7026: 7024: 7023: 7018: 7013: 7008: 7003: 6997: 6995: 6987: 6986: 6983: 6982: 6980: 6979: 6974: 6969: 6964: 6959: 6954: 6949: 6944: 6938: 6936: 6932: 6931: 6929: 6928: 6923: 6918: 6913: 6908: 6903: 6898: 6893: 6888: 6883: 6878: 6873: 6868: 6862: 6860: 6851: 6842: 6841: 6839: 6838: 6833: 6831:Word embedding 6828: 6823: 6818: 6811:Language model 6808: 6803: 6798: 6793: 6788: 6782: 6780: 6773: 6772: 6770: 6769: 6764: 6762:Transfer-based 6759: 6754: 6749: 6744: 6738: 6736: 6730: 6729: 6727: 6726: 6721: 6716: 6710: 6708: 6702: 6701: 6698: 6697: 6695: 6694: 6689: 6684: 6679: 6674: 6669: 6664: 6658: 6656: 6647: 6646: 6641: 6636: 6631: 6626: 6621: 6615: 6614: 6609: 6604: 6599: 6594: 6589: 6584: 6583: 6582: 6577: 6567: 6562: 6557: 6552: 6547: 6542: 6537: 6535:Concept mining 6532: 6527: 6521: 6519: 6513: 6512: 6510: 6509: 6504: 6499: 6494: 6489: 6488: 6487: 6482: 6472: 6467: 6461: 6459: 6455: 6454: 6447: 6446: 6439: 6432: 6424: 6415: 6414: 6412: 6411: 6406: 6401: 6396: 6391: 6389:Inverse filter 6386: 6381: 6376: 6370: 6368: 6364: 6363: 6361: 6360: 6355: 6350: 6345: 6340: 6335: 6330: 6325: 6320: 6314: 6312: 6306: 6305: 6303: 6302: 6297: 6292: 6286: 6284: 6280: 6279: 6277: 6276: 6271: 6266: 6261: 6256: 6251: 6246: 6241: 6235: 6233: 6229: 6228: 6226: 6225: 6220: 6215: 6210: 6205: 6200: 6195: 6190: 6184: 6182: 6178: 6177: 6174: 6173: 6171: 6170: 6165: 6160: 6155: 6150: 6145: 6140: 6135: 6130: 6125: 6120: 6115: 6109: 6107: 6103: 6102: 6100: 6099: 6094: 6089: 6084: 6079: 6074: 6069: 6064: 6059: 6054: 6049: 6044: 6039: 6034: 6029: 6024: 6018: 6016: 6009: 6001: 6000: 5997: 5996: 5994: 5993: 5988: 5983: 5977: 5975: 5971: 5970: 5968: 5967: 5962: 5957: 5948: 5943: 5938: 5933: 5923: 5921: 5914: 5908: 5907: 5900: 5899: 5892: 5885: 5877: 5868: 5867: 5865: 5864: 5859: 5854: 5848: 5846: 5840: 5839: 5837: 5836: 5831: 5825: 5823: 5817: 5816: 5814: 5813: 5808: 5803: 5801:Direct digital 5798: 5793: 5787: 5785: 5779: 5778: 5776: 5775: 5770: 5765: 5760: 5754: 5752: 5742: 5741: 5739: 5738: 5733: 5728: 5723: 5718: 5713: 5708: 5702: 5699: 5698: 5690: 5689: 5682: 5675: 5667: 5661: 5660: 5646: 5635: 5634:External links 5632: 5629: 5628: 5601: 5576: 5551: 5526: 5501: 5468: 5451:Suciu, Peter. 5443: 5418:Knibbs, Kate. 5410: 5385: 5360: 5335: 5305: 5275: 5254: 5229: 5202: 5187: 5157: 5142: 5112: 5075:(3): 214–231. 5055: 5025: 4999: 4977: 4952: 4921: 4887: 4857: 4832: 4811: 4790: 4768: 4747: 4722: 4695: 4688: 4680:Addison-Wesley 4663: 4648:"Amazon Polly" 4639: 4629:. folklore.org 4618: 4587: 4567: 4532: 4521:(2): 143–154. 4505: 4502:on 2013-07-03. 4479:(4): 278–287. 4456: 4438: 4420: 4399: 4385: 4352: 4327: 4295: 4275: 4245: 4230: 4183: 4162: 4122: 4081: 4036: 4011: 3986: 3953: 3928: 3903: 3873: 3843: 3822: 3758: 3733: 3695: 3647: 3640: 3622: 3557: 3537: 3515: 3495: 3479: 3463: 3438: 3421:. 1974-04-01. 3406: 3395:(2): 143–154. 3379: 3362: 3337: 3324: 3311: 3298: 3282: 3275: 3249: 3242: 3217: 3192: 3174: 3168:978-0992926007 3167: 3149: 3130: 3108: 3097: 3077: 3068: 3062: 3055: 3037: 3026:(3): 263–271. 3006: 2982: 2954: 2925: 2897:(4): 203–303. 2874: 2856: 2831: 2805: 2786: 2743: 2703: 2688: 2676: 2649: 2642: 2620: 2601:(2): 321–328. 2585: 2578: 2555: 2554: 2552: 2549: 2547: 2546: 2541: 2536: 2531: 2526: 2521: 2516: 2511: 2506: 2500: 2498: 2495: 2490: 2482: 2480: 2477: 2333:screen readers 2327: 2324: 2288: 2285: 2267:from the show 2239: 2238: 2223: 2216:near real-time 2212: 2188:Baidu Research 2164: 2161: 2160: 2159: 2149: 2131: 2117: 2106: 2099: 2096:enTourage eDGe 2082:, such as the 2080:e-book readers 2076: 2059: 2056: 2055: 2054: 2044: 2038: 2023: 2020: 1982:Google Toolbar 1961: 1958: 1949: 1946: 1940: 1937: 1916:Main article: 1913: 1910: 1853: 1850: 1797: 1794: 1781: 1778: 1754:Mac OS X Tiger 1730:Apple Computer 1695: 1692: 1655: 1652: 1626: 1623: 1602: 1599: 1565:Main article: 1562: 1559: 1554: 1551: 1550: 1549: 1544: 1534: 1529: 1514: 1511: 1464: 1461: 1452: 1449: 1428:pronunciations 1402: 1401: 1352: 1350: 1343: 1337: 1334: 1274: 1271: 1269: 1266: 1246:text-to-speech 1237:audio deepfake 1234: 1230:Audio deepfake 1226: 1224: 1221: 1141:Main article: 1138: 1135: 1123:Main article: 1120: 1117: 1084: 1081: 1034:Main article: 1031: 1028: 994:microprocessor 946: 943: 910:in words like 894: 891: 842: 839: 762: 759: 750:Main article: 747: 744: 711: 708: 645:Manbiki Shoujo 498:Bishnu S. Atal 433:Louis Gerstman 404: 401: 393:Alvin Liberman 360:developed the 356:In the 1930s, 290:(d. 1003 AD), 272: 269: 265:target prosody 230:prosodic units 216:pre-processing 132:text-to-speech 99: 93: 81: 76: 75: 74: 65: 64: 63: 58: 36: 30: 27: 25: 18:Text to speech 9: 6: 4: 3: 2: 7228: 7217: 7214: 7212: 7209: 7207: 7204: 7202: 7199: 7197: 7194: 7192: 7189: 7188: 7186: 7171: 7168: 7166: 7163: 7161: 7160:Hallucination 7158: 7156: 7153: 7152: 7150: 7146: 7140: 7137: 7135: 7132: 7130: 7127: 7124: 7120: 7117: 7115: 7112: 7111: 7109: 7107: 7101: 7095: 7094:Spell checker 7092: 7090: 7087: 7085: 7082: 7080: 7077: 7075: 7072: 7070: 7067: 7066: 7064: 7062: 7056: 7050: 7047: 7045: 7042: 7040: 7037: 7036: 7034: 7032: 7028: 7022: 7019: 7017: 7014: 7012: 7009: 7007: 7004: 7002: 6999: 6998: 6996: 6994: 6988: 6978: 6975: 6973: 6970: 6968: 6965: 6963: 6960: 6958: 6955: 6953: 6950: 6948: 6945: 6943: 6940: 6939: 6937: 6933: 6927: 6924: 6922: 6919: 6917: 6914: 6912: 6909: 6907: 6906:Speech corpus 6904: 6902: 6899: 6897: 6894: 6892: 6889: 6887: 6886:Parallel text 6884: 6882: 6879: 6877: 6874: 6872: 6869: 6867: 6864: 6863: 6861: 6855: 6852: 6847: 6843: 6837: 6834: 6832: 6829: 6827: 6824: 6822: 6819: 6816: 6812: 6809: 6807: 6804: 6802: 6799: 6797: 6794: 6792: 6789: 6787: 6784: 6783: 6781: 6778: 6774: 6768: 6765: 6763: 6760: 6758: 6755: 6753: 6750: 6748: 6747:Example-based 6745: 6743: 6740: 6739: 6737: 6735: 6731: 6725: 6722: 6720: 6717: 6715: 6712: 6711: 6709: 6707: 6703: 6693: 6690: 6688: 6685: 6683: 6680: 6678: 6677:Text chunking 6675: 6673: 6670: 6668: 6667:Lemmatisation 6665: 6663: 6660: 6659: 6657: 6655: 6651: 6645: 6642: 6640: 6637: 6635: 6632: 6630: 6627: 6625: 6622: 6620: 6617: 6616: 6613: 6610: 6608: 6605: 6603: 6600: 6598: 6595: 6593: 6590: 6588: 6585: 6581: 6578: 6576: 6573: 6572: 6571: 6568: 6566: 6563: 6561: 6558: 6556: 6553: 6551: 6548: 6546: 6543: 6541: 6538: 6536: 6533: 6531: 6528: 6526: 6523: 6522: 6520: 6518: 6517:Text analysis 6514: 6508: 6505: 6503: 6500: 6498: 6495: 6493: 6490: 6486: 6483: 6481: 6478: 6477: 6476: 6473: 6471: 6468: 6466: 6463: 6462: 6460: 6458:General terms 6456: 6452: 6445: 6440: 6438: 6433: 6431: 6426: 6425: 6422: 6410: 6409:Voice cloning 6407: 6405: 6402: 6400: 6399:Phase vocoder 6397: 6395: 6392: 6390: 6387: 6385: 6382: 6380: 6377: 6375: 6372: 6371: 6369: 6365: 6359: 6356: 6354: 6351: 6349: 6346: 6344: 6341: 6339: 6336: 6334: 6331: 6329: 6326: 6324: 6321: 6319: 6318:Alan W. Black 6316: 6315: 6313: 6307: 6301: 6298: 6296: 6293: 6291: 6288: 6287: 6285: 6281: 6275: 6272: 6270: 6267: 6265: 6262: 6260: 6257: 6255: 6252: 6250: 6247: 6245: 6242: 6240: 6237: 6236: 6234: 6230: 6224: 6221: 6219: 6216: 6214: 6211: 6209: 6206: 6204: 6201: 6199: 6196: 6194: 6191: 6189: 6186: 6185: 6183: 6179: 6169: 6166: 6164: 6161: 6159: 6156: 6154: 6151: 6149: 6146: 6144: 6141: 6139: 6136: 6134: 6131: 6129: 6126: 6124: 6121: 6119: 6116: 6114: 6111: 6110: 6108: 6104: 6098: 6095: 6093: 6090: 6088: 6085: 6083: 6080: 6078: 6075: 6073: 6070: 6068: 6065: 6063: 6062:Voice browser 6060: 6058: 6055: 6053: 6050: 6048: 6045: 6043: 6040: 6038: 6035: 6033: 6030: 6028: 6025: 6023: 6020: 6019: 6017: 6013: 6010: 6008: 6002: 5992: 5989: 5987: 5984: 5982: 5979: 5978: 5976: 5972: 5966: 5963: 5961: 5958: 5956: 5952: 5949: 5947: 5944: 5942: 5939: 5937: 5934: 5932: 5928: 5925: 5924: 5922: 5918: 5915: 5913: 5912:Free software 5909: 5905: 5898: 5893: 5891: 5886: 5884: 5879: 5878: 5875: 5863: 5860: 5858: 5855: 5853: 5850: 5849: 5847: 5845: 5841: 5835: 5832: 5830: 5827: 5826: 5824: 5822: 5818: 5812: 5809: 5807: 5804: 5802: 5799: 5797: 5794: 5792: 5789: 5788: 5786: 5784: 5780: 5774: 5773:Concatenative 5771: 5769: 5766: 5764: 5761: 5759: 5756: 5755: 5753: 5751: 5747: 5743: 5737: 5734: 5732: 5729: 5727: 5724: 5722: 5719: 5717: 5714: 5712: 5709: 5707: 5704: 5703: 5700: 5695: 5688: 5683: 5681: 5676: 5674: 5669: 5668: 5665: 5658: 5654: 5650: 5647: 5645: 5641: 5638: 5637: 5623: 5618: 5614: 5613: 5605: 5590: 5586: 5580: 5565: 5561: 5555: 5540: 5536: 5530: 5516: 5512: 5505: 5491: 5487: 5483: 5479: 5472: 5458: 5454: 5447: 5433: 5429: 5425: 5421: 5414: 5400: 5396: 5389: 5374: 5370: 5364: 5349: 5345: 5339: 5324: 5320: 5316: 5309: 5294: 5290: 5286: 5279: 5264: 5258: 5243: 5239: 5233: 5225: 5221: 5220: 5212: 5206: 5198: 5194: 5190: 5184: 5180: 5176: 5172: 5168: 5161: 5153: 5149: 5145: 5139: 5135: 5131: 5127: 5123: 5116: 5108: 5104: 5100: 5096: 5091: 5086: 5082: 5078: 5074: 5070: 5066: 5059: 5045:on 2020-08-07 5044: 5040: 5036: 5029: 5016: 5012: 5011: 5003: 4988: 4981: 4967: 4963: 4956: 4941: 4937: 4936: 4931: 4925: 4917: 4912: 4908: 4904: 4903: 4898: 4891: 4883: 4878: 4875:: 4485–4495, 4874: 4870: 4869: 4861: 4847:on 2013-10-03 4846: 4842: 4836: 4821: 4815: 4808: 4807:0-7695-2932-1 4804: 4800: 4794: 4779: 4772: 4757: 4751: 4736: 4732: 4726: 4710: 4706: 4699: 4691: 4685: 4681: 4677: 4673: 4667: 4653: 4649: 4643: 4628: 4622: 4608:on 2012-03-24 4604: 4597: 4591: 4584: 4580: 4577: 4571: 4563: 4559: 4555: 4551: 4547: 4543: 4536: 4528: 4524: 4520: 4516: 4509: 4498: 4494: 4490: 4486: 4482: 4478: 4474: 4467: 4460: 4452: 4451:Science Daily 4448: 4442: 4434: 4430: 4424: 4410:. Festvox.org 4409: 4403: 4395: 4389: 4375: 4371: 4367: 4363: 4356: 4342: 4338: 4331: 4317: 4313: 4309: 4305: 4299: 4286: 4282: 4278: 4272: 4268: 4264: 4260: 4256: 4249: 4241: 4234: 4226: 4222: 4218: 4214: 4210: 4206: 4202: 4198: 4194: 4187: 4173: 4169: 4165: 4159: 4155: 4151: 4146: 4141: 4137: 4133: 4126: 4118: 4112: 4104: 4100: 4096: 4092: 4085: 4077: 4073: 4069: 4065: 4060: 4055: 4051: 4047: 4040: 4026: 4022: 4015: 4001: 3997: 3990: 3976: 3972: 3968: 3964: 3961:WIRED Staff. 3957: 3943: 3939: 3932: 3917: 3913: 3907: 3892: 3888: 3884: 3877: 3862: 3858: 3854: 3847: 3838: 3833: 3826: 3812:on 2011-12-16 3808: 3804: 3800: 3796: 3792: 3788: 3784: 3780: 3776: 3769: 3762: 3748:on 2012-02-13 3747: 3743: 3737: 3729: 3725: 3721: 3717: 3713: 3709: 3702: 3700: 3684: 3680: 3676: 3672: 3668: 3661: 3654: 3652: 3643: 3637: 3633: 3626: 3619: 3615: 3611: 3607: 3603: 3599: 3595: 3591: 3587: 3583: 3579: 3575: 3571: 3567: 3561: 3555: 3551: 3547: 3546:Astro Blaster 3541: 3534: 3530: 3527: 3526: 3519: 3512: 3508: 3504: 3499: 3491: 3490: 3483: 3475: 3474: 3467: 3452: 3448: 3442: 3428: 3424: 3420: 3416: 3410: 3402: 3398: 3394: 3390: 3383: 3376: 3372: 3366: 3351: 3347: 3341: 3334: 3328: 3321: 3318:Julia Zhang. 3315: 3308: 3307:Alan W. Black 3302: 3295: 3291: 3290:Alan W. 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