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Whisper is an automatic speech recognition (asr) system trained on 680,000 hours of multilingual and multitask supervised data collected from the web Whisper は、ウェブから収集された68万時間に及ぶ多言語・マルチタスクの教師ありデータに基づいて学習した自動音声認識（ASR）システムです。 We show that the use of such a large and diverse dataset leads to improved robustness to accents, background noise and technical language.

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One of the most common challenges faced when using whisper is the model often does not recognize uncommon words or acronyms You can also use it as a multitask model to perform multilingual speech recognition as well as speech translation and language identification. Here are some different techniques to improve the reliability of whisper in these cases:

Hemos entrenado una red neuronal de código abierto llamada whisper que se acerca a la capacidad y la precisión humanas en el reconocimiento de voz en inglés.

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