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  2. Help:IPA/Nguni - Wikipedia

    en.wikipedia.org/wiki/Help:IPA/Nguni

    The charts below show the way in which the IPA is used to transcribe the Nguni languages Swazi, Xhosa, and Zulu.For a guide to adding IPA characters to Wikipedia articles, see Template:IPA and Wikipedia:Manual of Style/Pronunciation § Entering IPA characters.

  3. Template:IPA - Wikipedia

    en.wikipedia.org/wiki/Template:IPA

    Name of an audio file to accompany the transcription. label Text that precedes the transcription. Takes precedence over the third unnamed parameter. link If set to yes, the language name in the label will be linked to the article about the language. small If set to no, the label appears in the

  4. Transcription software - Wikipedia

    en.wikipedia.org/wiki/Transcription_software

    Compared with audio content, a text transcript is searchable, takes up less computer memory, and can be used as an alternate method of communication, such as for subtitles and closed captions. The definition of transcription "software", as compared with transcription "service", is that the former is sufficiently automated that a user can run ...

  5. Google Translate - Wikipedia

    en.wikipedia.org/wiki/Google_Translate

    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]

  6. Category:Articles containing Zulu-language text - Wikipedia

    en.wikipedia.org/wiki/Category:Articles...

    This category contains articles with Zulu-language text. The primary purpose of these categories is to facilitate manual or automated checking of text in other languages. This category should only be added with the {} family of templates, never explicitly.

  7. Whisper (speech recognition system) - Wikipedia

    en.wikipedia.org/wiki/Whisper_(speech...

    Whisper is a machine learning model for speech recognition and transcription, created by OpenAI and first released as open-source software in September 2022. [2]It is capable of transcribing speech in English and several other languages, and is also capable of translating several non-English languages into English. [1]

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