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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 (vocoder). Deep neural networks (DNN) 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.
A text-to-speech (TTS) system converts normal language text into speech; other systems render symbolic linguistic representations like phonetic transcriptions into speech. [1] The reverse process is speech recognition. Synthesized speech can be created by concatenating pieces of recorded speech that are stored in a database.
FreeTTS is an open source speech synthesis system written entirely in the Java programming language. It is based upon Flite. FreeTTS is an implementation of Sun 's Java Speech API . FreeTTS supports end-of-speech markers. Gnopernicus uses these in a number of places: to know when text should and should not be interrupted, to better concatenate ...
WaveNet is a deep neural network for generating raw audio. It was created by researchers at London-based AI firm DeepMind.The technique, outlined in a paper in September 2016, is able to generate relatively realistic-sounding human-like voices by directly modelling waveforms using a neural network method trained with recordings of real speech.
15.ai is a non-commercial freeware artificial intelligence web application that generates natural emotive high-fidelity [a] text-to-speech voices from an assortment of fictional characters from a variety of media sources.
eSpeak. 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. Because of its small size and many ...
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