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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.
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 ...
This is an accepted version of this page This is the latest accepted revision, reviewed on 21 December 2024. 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 ...
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
Generative AI can also be trained extensively on audio clips to produce natural-sounding speech synthesis and text-to-speech capabilities, exemplified by ElevenLabs' context-aware synthesis tools or Meta Platform's Voicebox. [55] AI-generated music from the Riffusion Inference Server, prompted with bossa nova with electric guitar
Most voice synthesizers (including Apple's Siri) use concatenative synthesis, [5] in which a program stores individual phonemes and then pieces them together to form words and sentences. WaveNet synthesizes speech with human-like emphasis and inflection on syllables, phonemes, and words. Unlike most other text-to-speech systems, a WaveNet model ...
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