Whisper is an automatic speech recognition (ASR) system developed by OpenAI, designed for high robustness and accuracy using a vast, diverse dataset.

What languages can Whisper transcribe?

Whisper can transcribe speech in multiple languages and translate these languages into English.

How does Whisper handle input audio?

Input audio is split into 30-second chunks, converted into log-Mel spectrograms, and then passed into an encoder to predict text captions.

What are the special tokens used for in Whisper?

Special tokens in Whisper are used for language identification, phrase-level timestamps, multilingual speech transcription, and translation into English.

How does Whisper compare to existing ASR systems?

Whisper is more robust, with 50% fewer errors in zero-shot performance across diverse datasets due to its large and diverse training dataset.

Is Whisper specialized for certain benchmarks?

While Whisper doesn't excel in specialized benchmarks like LibriSpeech, it outperforms state-of-the-art models in zero-shot translations on datasets like CoVoST2.

What resources are available for Whisper?

OpenAI has made the paper, model card, and code for Whisper available for more detailed understanding and experimentation.

What impact does Whisper aim to have?

Whisper aims to enable developers to add voice interfaces easily to various applications due to its high accuracy and ease of use.

Try out our new FREE Youtube Summarizer!

Whisper (OpenAI)

Name: Whisper (OpenAI)
Brand: Whisper (OpenAI)
Rating: 5 (1 reviews)
Author: Whisper (OpenAI)

Claim Tool

Last updated: August 8, 2024

0 reviews

What is Whisper (OpenAI)?

Whisper is a cutting-edge automatic speech recognition (ASR) system created by OpenAI. Trained on 680,000 hours of multilingual and multitask supervised data from the web, Whisper boasts improved robustness to accents, background noise, and technical language. It provides transcription services in multiple languages and translates those languages into English. Whisper uses an encoder-decoder Transformer architecture that captures 30-second audio chunks, converts them to log-Mel spectrograms, and predicts corresponding text captions. Its large and diverse dataset helps Whisper outperform existing systems in zero-shot performance across diverse scenarios.