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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.
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.
Natural language processing (NLP) is a subfield of computer science and especially artificial intelligence.It is primarily concerned with providing computers with the ability to process data encoded in natural language and is thus closely related to information retrieval, knowledge representation and computational linguistics, a subfield of linguistics.
This is an accepted version of this page This is the latest accepted revision, reviewed on 26 February 2025. Artificial production of human speech Automatic announcement A synthetic voice announcing an arriving train in Sweden. Problems playing this file? See media help. Speech synthesis is the artificial production of human speech. A computer system used for this purpose is called a speech ...
During training, the network extracts the underlying structure of the speech, such as which tones follow each other and what a realistic speech waveform looks like. When given a text input, the trained WaveNet model can generate the corresponding speech waveforms from scratch, one sample at a time, with up to 24,000 samples per second and ...
Name Creator(s) First public release date Latest stable version Software license; 15.ai: 15: 2020 2022 Apple PlainTalk: Apple Inc. 1984 2018 Bundled with Mac OS X: AT&T Natural Voices
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.
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.
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