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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.
There are many languages (notably English) which do not have straightforward one-to-one rules between writing and pronunciation; therefore, the first step in text-to-speech generation has to be text-to-phoneme translation. input text is translated into pronunciation phonemes (e.g. input text xerox is translated into zi@r0ks for pronunciation).
A new, much more natural-sounding voice, called "Alex" has been added to the Mac text-to-speech roster with the release of Mac OS X 10.5 Leopard. [5] With Mac OS X 10.7 Lion, voices are available in additional U.S. English and other English accents, as well as 21 other languages. [6]
This is an accepted version of this page This is the latest accepted revision, reviewed on 31 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 ...
“That’s not to say we aren’t going to see a trend toward people actually starting to use the ‘influencer accent’ in real life. People copy the speech patterns of people they look up to ...
The International Phonetic Alphabet (IPA) can be used to represent sound correspondences among various accents and dialects of the English language. These charts give a diaphoneme for each sound, followed by its realization in different dialects.
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