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  2. Otter.ai - Wikipedia

    en.wikipedia.org/wiki/Otter.ai

    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]

  3. Transcription software - Wikipedia

    en.wikipedia.org/wiki/Transcription_software

    New software-as-a-service and cloud computing models use artificial intelligence, machine learning and natural language processing to convert speech to text and continuously learn new phrases and accents. [3] AI transcription can, however, lead to hallucinations and other errors. [4] [5] [6] [7]

  4. 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]

  5. This AI can transcribe recorded and live speech into text ...

    www.aol.com/news/ai-transcribe-recorded-live...

    TL;DR: As of March 4, a lifetime subscription to Voicetapp Speech to Text Transcription is on sale for $59 — that's over 90% in savings.Transcribing audio is one of those tasks that is tedious ...

  6. 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).

  7. Neural machine translation - Wikipedia

    en.wikipedia.org/wiki/Neural_machine_translation

    These models differ from an encoder-decoder NMT system in a number of ways: [35]: 1 Generative language models are not trained on the translation task, let alone on a parallel dataset. Instead, they are trained on a language modeling objective, such as predicting the next word in a sequence drawn from a large dataset of text.

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