Whisper is an automatic speech recognition (ASR) system trained on 680,000 hours of multilingual and multitask supervised data collected from the web. We show that the use of such a large and diverse dataset leads to improved robustness to accents, background noise and technical language. Moreover, it enables transcription in multiple languages, as well as translation from those languages into English.
What is Whisper by Open AI?
Automatic speech recognition (ASR) technology is a form of artificial intelligence that allows computers to recognize, transcribe, and understand spoken language. Whisper is a type of ASR technology that is specifically designed to recognize and transcribe speech that is spoken quietly or softly.
One of the main challenges in ASR technology is accurately transcribing speech that is difficult to hear or understand. Whisper addresses this challenge by using advanced machine learning algorithms to analyze and interpret soft or quiet speech. These algorithms are trained on large datasets of spoken language and use pattern recognition to identify the sounds and words that make up human speech.
Whisper is particularly useful in environments where it is difficult to hear or understand spoken language, such as in crowded or noisy rooms. It can also be useful in situations where the speaker is intentionally trying to speak softly or quietly, such as in a library or other quiet setting.
In addition to recognizing and transcribing spoken language, Whisper can also be used to analyze the content of speech and extract useful information. For example, it could be used to identify key phrases or topics discussed in a conversation, or to identify the sentiment or emotion behind the words being spoken.
Overall, Whisper is a powerful and useful tool for anyone who needs to transcribe or understand spoken language, particularly in challenging environments. It has the potential to revolutionize the way we communicate and interact with computers and other devices, making it easier and more natural to communicate with machines using our natural voice.
