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DECtalk demo recording using the Perfect Paul and Uppity Ursula voices. DECtalk [4] was a speech synthesizer and text-to-speech technology developed by Digital Equipment Corporation in 1983, [1] based largely on the work of Dennis Klatt at MIT, whose source-filter algorithm was variously known as KlattTalk or MITalk.
It was first created in the English language [2] and the English WordNet database and software tools have been released under a BSD style license and are freely available for download. The latest official release from Princeton was released in 2011 [ citation needed ] .
It is necessary to collect clean and well-structured raw audio with the transcripted text of the original speech audio sentence. Second, the text-to-speech model must be trained using these data to build a synthetic audio generation model. Specifically, the transcribed text with the target speaker's voice is the input of the generation model.
eSpeak is a free and open-source, cross-platform, compact, software speech synthesizer.It uses a formant synthesis method, providing many languages in a relatively small file size. eSpeakNG (Next Generation) is a continuation of the original developer's project with more feedback from native speakers.
Linear predictive coding (LPC) is a speech coding method used in speaker recognition and speech verification. [citation needed] Ambient noise levels can impede both collections of the initial and subsequent voice samples. Noise reduction algorithms can be employed to improve accuracy, but incorrect application can have the opposite effect.
No longer supported for versions above Windows Vista. [11] Untested above macOS 10.4 or on Macintoshes with an Intel chipset. [12] Quack.com; acquired by AOL; the name has now been reused for an iPad search app. SpeechWorks from Nuance Communications. Yap Speech Cloud – Speech-to-text platform acquired by Amazon.com.
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Deep learning speech synthesis refers to the application of deep learning models to generate natural-sounding human speech from written text (text-to-speech) or spectrum . Deep neural networks are trained using large amounts of recorded speech and, in the case of a text-to-speech system, the associated labels and/or input text.
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