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Text normalization is frequently used when converting text to speech. Numbers, dates, acronyms, and abbreviations are non-standard "words" that need to be pronounced differently depending on context. [2] For example: "$200" would be pronounced as "two hundred dollars" in English, but as "lua selau tālā" in Samoan. [3]
Text-to-Speech may be used by apps such as Google Play Books for reading books aloud, Google Translate for reading aloud translations for the pronunciation of words, Google TalkBack, and other spoken feedback accessibility-based applications, as well as by third-party apps. Users must install voice data for each language.
Google Translate is a multilingual neural machine translation service developed by Google to translate text, documents and websites from one language into another. It offers a website interface, a mobile app for Android and iOS, as well as an API that helps developers build browser extensions and software applications. [3]
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 ...
The remaining steps convert the spoken text to speech: Text-to-phoneme conversion: Converts each word to phonemes. A phoneme is a basic unit of sound in a language. Prosody analysis: Processes the sentence structure, words, and phonemes to determine the appropriate prosody for the sentence.
For desktop applications, other markup languages are popular, including Apple's embedded speech commands, and Microsoft's SAPI Text to speech (TTS) markup, also an XML language. It is also used to produce sounds via Azure Cognitive Services' Text to Speech API or when writing third-party skills for Google Assistant or Amazon Alexa.
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 .
NETtalk was created to explore the mechanisms of learning to correctly pronounce English text. The authors note that learning to read involves a complex mechanism involving many parts of the human brain. NETtalk does not specifically model the image processing stages and letter recognition of the visual cortex.