Multimodality · 2022
Robust Speech Recognition via Large-Scale Weak Supervision (Whisper)
Trained a single speech model on a very large, weakly-labeled multilingual corpus, achieving robust zero-shot transcription and translation without dataset-specific fine-tuning.
Editorial record
Plain-language summary
Whisper is an encoder-decoder Transformer trained on hundreds of thousands of hours of diverse audio-text pairs scraped from the web, covering many languages and tasks in one model. It approaches specialized systems zero-shot and is resilient to accents and noise. Its open release made strong speech recognition broadly available.
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Descendants
Depends onEvidence: Direct
Attention Is All You Need
Whisper is an encoder-decoder Transformer for speech
P-531
Source record
Provenance
- Record ID
- P-531
- Record created
- 2026-07-13
- Last reviewed
- 2026-07-14
- Record version
- 2
- https://arxiv.org/abs/2212.04356
- arXiv:2212.04356
Citation caveat: Citation metadata is approximate and marked unverified in the source dataset.