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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.
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.
In early 2020, 15.ai appeared online as a proof of concept of the democratization of voice acting and dubbing. [8] [11] Its gratis nature, ease of use without user accounts, and improvements over existing text-to-speech implementations made it popular.
This is an accepted version of this page This is the latest accepted revision, reviewed on 2 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 ...
Apps such as textPlus and WhatsApp use Text-to-Speech to read notifications aloud and provide voice-reply functionality. Google Cloud Text-to-Speech is powered by WaveNet, [5] software created by Google's UK-based AI subsidiary DeepMind, which was bought by Google in 2014. [6] It tries to distinguish from its competitors, Amazon and Microsoft. [7]
Google announced that Google Translate can now also translate without transcribing, using neural networks. This means that it is possible to translate speech in one language directly into text in another language, without first transcribing it to text.
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