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2. 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]

3. National Library Service for the Blind and Print Disabled

   en.wikipedia.org/wiki/National_Library_Service...

   The National Library Service for the Blind and Print Disabled [1] (NLS) is a free library program of braille and audio materials such as books and magazines circulated to eligible borrowers in the United States and American citizens living abroad by postage-free mail and online download. The program is sponsored by the Library of Congress.

4. List of speech recognition software - Wikipedia

   en.wikipedia.org/wiki/List_of_speech_recognition...

   Application name Description Open-source License Price Note Assistant.ai: Assistant for Android, iOS and Windows Phone: No: Proprietary, freeware: Free: Discontinued Dragon Dictation

5. Researchers say an AI-powered transcription tool used in ...

   www.aol.com/researchers-ai-powered-transcription...

   A University of Michigan researcher conducting a study of public meetings, for example, said he found hallucinations in eight out of every 10 audio transcriptions he inspected, before he started ...

6. LibriVox - Wikipedia

   en.wikipedia.org/wiki/LibriVox

   LibriVox is an invented word inspired by Latin words liber (book) in its genitive form libri and vox (voice), giving the meaning BookVoice (or voice of the book). The word was also coined because of other connotations: liber also means child and free, independent, unrestricted. As the LibriVox forum says: "We like to think LibriVox might be ...

7. Automated medical scribe - Wikipedia

   en.wikipedia.org/wiki/Automated_medical_scribe

   Like other LLMs, medical-scribe LLMs are prone to confabulation, where they make up content based on statistically associations between their training data and the transcription audio. [3] LLMs do not distinguish between trying to transcribe the audio and guessing what words will come next, but perform both processes mixed together. [18]