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Some users have also created AI virtual assistants using 15.ai and external voice control software. [51] [52] Text-to-speech is also used in second language acquisition. Voki, for instance, is an educational tool created by Oddcast that allows users to create their own talking avatar, using different accents.
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.
Retrieval-based Voice Conversion (RVC) is an open source voice conversion AI algorithm that enables realistic speech-to-speech transformations, accurately preserving the intonation and audio characteristics of the original speaker.
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]
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.
The major steps in producing speech from text are as follows: Structure analysis: Processes the input text to determine where paragraphs, sentences, and other structures start and end. For most languages, punctuation and formatting data are used in this stage. Text pre-processing: Analyzes the input text for special constructs of the language.
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