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  2. Speech-to-text reporter - Wikipedia

    en.wikipedia.org/wiki/Speech-to-text_reporter

    A speech-to-text reporter (STTR), also known as a captioner, is a person who listens to what is being said and inputs it, word for word (), as properly written texts.Many captioners use tools (such as a shorthand keyboard, speech recognition software, or a computer-aided transcription software system), which commonly convert verbally communicated information into written words to be composed ...

  3. Speech recognition - Wikipedia

    en.wikipedia.org/wiki/Speech_recognition

    Speech recognition is an interdisciplinary subfield of computer science and computational linguistics that develops methodologies and technologies that enable the recognition and translation of spoken language into text by computers. It is also known as automatic speech recognition (ASR), computer speech recognition or speech-to-text (STT).

  4. Transcription software - Wikipedia

    en.wikipedia.org/wiki/Transcription_software

    With speech recognition technology, transcriptionists can automatically convert recordings to text transcripts by opening recordings in a PC and uploading them to a cloud for automatic transcription, or transcribe recordings in real-time by using digital dictation. Depending on quality of recordings, machine generated transcripts may still need ...

  5. Common Voice - Wikipedia

    en.wikipedia.org/wiki/Common_Voice

    Common Voice is a crowdsourcing project started by Mozilla to create a free database for speech recognition software.The project is supported by volunteers who record sample sentences with a microphone and review recordings of other users.

  6. TIMIT - Wikipedia

    en.wikipedia.org/wiki/TIMIT

    TIMIT is a corpus of phonemically and lexically transcribed speech of American English speakers of different sexes and dialects. Each transcribed element has been delineated in time. TIMIT was designed to further acoustic-phonetic knowledge and automatic speech recognition systems.

  7. DARPA Global autonomous language exploitation program

    en.wikipedia.org/wiki/DARPA_Global_autonomous...

    The program encompassed three main challenges: automatic speech recognition, machine translation, and information retrieval. [1] The focus of the program was on recognizing speech in Mandarin and Arabic and translating it to English. Teams led by IBM, BBN (led by John Makhoul), and SRI participated in the program. [2]

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