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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.
Text-to-speech (TTS) refers to the ability of computers to read text aloud. A TTS engine converts written text to a phonemic representation, then converts the phonemic representation to waveforms that can be output as sound. TTS engines with different languages, dialects and specialized vocabularies are available through third-party publishers ...
TL;DR: As of March 12, a lifetime subscription to TexTalky AI Text-to-Speech, worth $540 is 93% off, so you can get it for just $37.From marketing content and video narration to customer support ...
Speech synthesis includes text-to-speech, which aims to transform the text into acceptable and natural speech in real-time, [33] making the speech sound in line with the text input, using the rules of linguistic description of the text. A classical system of this type consists of three modules: a text analysis model, an acoustic model, and a ...
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]
Festival Speech Synthesis System: CSTR? 2014, December MIT-like license: FreeTTS: Paul Lamere Philip Kwok Dirk Schnelle-Walka Willie Walker... 2001, December 14 2009, March 9 BSD: LumenVox: LumenVox: 2011 2019 Proprietary: Microsoft Speech API: Microsoft: 1995 2012 Bundled with Windows: VoiceText: ReadSpeaker (Formerly Neospeech) 2002 2017 ...
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