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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.
This is an accepted version of this page This is the latest accepted revision, reviewed on 17 January 2025. 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 ...
AT&T Natural Voices: AT&T Natural Voices? 2008 Proprietary: Polly: Amazon AWS 2016 2019 Proprietary: Cepstral: Cepstral 2000 2013 Proprietary: CereProc: CereProc 2006 2017, February Proprietary: eSpeak: Jonathan Duddington 2006, February 10 2022, April 3 GPLv3+ Festival Speech Synthesis System: CSTR? 2014, December MIT-like license: FreeTTS ...
None of these voices match the Cortana text-to-speech voice which can be found on Windows Phone 8.1, Windows 10, and Windows 10 Mobile. In an attempt to unify its software with Windows 10, all of Microsoft's current platforms use the same text-to-speech voices except for Microsoft David and a few others.
It is necessary to collect clean and well-structured raw audio with the transcripted text of the original speech audio sentence. Second, the text-to-speech model must be trained using these data to build a synthetic audio generation model. Specifically, the transcribed text with the target speaker's voice is the input of the generation model.
CereProc mined tapes and DVD commentaries featuring Ebert's voice to create a text-to-speech voice that sounded more like his own. [4] Roger Ebert used the voice in his March 2, 2010, appearance on The Oprah Winfrey Show. NFL player Steve Gleason had his voice cloned by CereProc following his diagnosis with MND.
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