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. The model uses a neural network that has been trained using a large volume of speech samples. Unlike most other text-to-speech systems, a WaveNet model creates raw audio waveforms from scratch. On average, a WaveNet produces speech audio that people prefer over other text-to-speech technologies. It synthesizes speech with more human-like emphasis and inflection on syllables, phonemes, and words. Most voice synthesizers (including Apple's Siri) use concatenative synthesis, in which a program stores individual phonemes and then pieces them together to form words and sentences.Ī WaveNet generates speech that sounds more natural than other text-to-speech systems. ĭeepMind's AI voice synthesis tech is notably advanced and realistic. It tries to distinguish from its competitors, Amazon and Microsoft, with distinct AI features. Google Cloud Text-to-Speech is powered by WaveNet, software created by Google's UK-based AI subsidiary DeepMind, which was bought by Google in 2014. Apps such as textPlus and WhatsApp use Text-to-Speech to read notifications aloud and provide voice-reply functionality.

Some app developers have started adapting and tweaking their Android Auto apps to include Text-to-Speech, such as Hyundai in 2015. Please help improve this article by introducing citations to additional sources. Relevant discussion may be found on the talk page. This section relies largely or entirely on a single source.

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