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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]
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]
Transcription software, as with transcription services, is often provided for business, legal, or medical purposes. 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.
One of these is Snipd, a Swiss startup building a podcast app that uses AI to transcribe content and synchronize with note-taking apps, automatically generate book-style "chapters" and, as of this ...
Otter.ai, Inc. is an American transcription software company based in Mountain View, California. The company develops speech to text transcription applications using artificial intelligence and machine learning. Its software, called Otter, shows captions for live speakers, and generates written transcriptions of speech. [1]
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).
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