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Research at Google released a free android app Google Live Transcribe, it runs on Google Cloud. [8] [9] Google Chrome developed and has an available built in English Live Caption. [10] Google Docs, Google Translate, Google Assistant, GBoard Google Text to Speech engine support transcription tool too. [11] [12] [13] [14]
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]
Speech recognition is an interdisciplinary subfield of computer science and computational linguistics that develops methodologies and technologies that enable the recognition and translation of spoken language into text by computers. It is also known as automatic speech recognition (ASR), computer speech recognition or speech-to-text (STT).
Key features include a Multimodal Live API for real-time audio and video interactions, enhanced spatial understanding, native image and controllable text-to-speech generation (with watermarking), and integrated tool use, including Google Search. [42]
In June 2018, Google proposed to use pre-trained speaker verification models as speaker encoders to extract speaker embeddings. [14] The speaker encoders then become part of the neural text-to-speech models, so that it can determine the style and characteristics of the output speech.
In December 2017, Google researchers published a preprint paper on replacing the Codec 2 decoder with a WaveNet neural network. They found that a neural network is able to extrapolate features of the voice not described in the Codec 2 bitstream and give better audio quality, and that the use of conventional features makes the neural network calculation simpler compared to a purely waveform ...
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