inference/research
verifiedhigh · 0.85updated 2026-10-04

Whisper: Robust Speech Recognition via Large-Scale Weak Supervision

speech · icml

Fields

id
papers/whisper
arXiv
2212.04356
Venue
icml
Venue track
main
Year
2023
Category
speech
Adoption
in-production
Authors
Alec RadfordJong Wook KimTao XuGreg BrockmanChristine McLeaveyIlya Sutskever
Affiliations
OpenAI
Problem
Supervised ASR requires per-domain labelled audio, so one model cannot cover many domains and noisy conditions without retraining.
Mechanism
Multitask encoder-decoder Transformer trained on 680k hours of weakly labelled internet audio with a multitask 'tokens, timestamp, language' objective: the decoder is conditioned on a detected source language, which forces it to also act as a language identifier and produces per-language training data for free. Trained with 30s windows of log-Mel spectrogram at 16 kHz, so inference always operates on a fixed 30s context regardless of the true utterance length.
Open weights
yes
notes
Venue confirmed against the PMLR v202 table of contents: 'Proceedings of the 40th International Conference on Machine Learning, PMLR 202:28492-28518'. arXiv posted Dec 2022, venue 2023. This is the highest-adoption speech model in the repo: shipped as the OpenAI speech-to-text API, vendored by Apple (iOS/macOS dictation), Unity, and reachable from most cloud STT wrappers. INFERENCE-COST NOTE that matters more than the accuracy numbers: the fixed 30s context means short utterances pay for the whole window. Encoder prefill is over 3000 mel frames regardless of utterance length, so a 1-second utterance and a 30-second utterance cost nearly the same. Chunked long-form inference (30s slices) plus local agreement (Whisper-Streaming, 2307.14743) or chunk-aware batching is the standard mitigation. Decoder output token count, not audio length, is what varies. The paper reports no wall-clock latency or hardware throughput numbers, hence speedup_reported is null. YEAR FIELD CORRECTION 2026-10-04 (paper-fields pass, agent w3p): year 2022 -> 2023. The record's own notes already said the venue year is 2023 ('PMLR 202:28492-28518') while the field carried 2022, so the field and the note disagreed and the note was right. EVIDENCE re-checked 2026-10-04 against the static PMLR table of contents: v202 is the 40th ICML, 23-29 July 2023 (read off the volume landing page header, not assumed), and the volume contains the title verbatim. BOTH VALUES RETAINED per the repo contract: 2022 was the previous field value and is the arXiv posting year (published 2022-12-17), which is still a true statement about the preprint. arxiv_id unchanged (2212.04356). status set to contested because this changes a published attribution. 2026-10-10: PMLR v202 ICML 2023 proceedings (idx1.py: https://proceedings.mlr.press/v202/) confirms "Robust Speech Recognition via Large-Scale Weak Supervision" (Radford et al., PMLR 202:28492-28518). arXiv API 2212.04356 (axc.py) submission verified. Source pap-mm-whisper notes cite PMLR v202:28492-28518 and PMLR v202 confirms ICML 2023 (in venue enum). Status resolved to verified.

Notes

Venue confirmed against the PMLR v202 table of contents: 'Proceedings of the 40th International Conference on Machine Learning, PMLR 202:28492-28518'. arXiv posted Dec 2022, venue 2023. This is the highest-adoption speech model in the repo: shipped as the OpenAI speech-to-text API, vendored by Apple (iOS/macOS dictation), Unity, and reachable from most cloud STT wrappers. INFERENCE-COST NOTE that matters more than the accuracy numbers: the fixed 30s context means short utterances pay for the whole window. Encoder prefill is over 3000 mel frames regardless of utterance length, so a 1-second utterance and a 30-second utterance cost nearly the same. Chunked long-form inference (30s slices) plus local agreement (Whisper-Streaming, 2307.14743) or chunk-aware batching is the standard mitigation. Decoder output token count, not audio length, is what varies. The paper reports no wall-clock latency or hardware throughput numbers, hence speedup_reported is null.

YEAR FIELD CORRECTION 2026-10-04 (paper-fields pass, agent w3p): year 2022 -> 2023. The record's own notes already said the venue year is 2023 ('PMLR 202:28492-28518') while the field carried 2022, so the field and the note disagreed and the note was right. EVIDENCE re-checked 2026-10-04 against the static PMLR table of contents: v202 is the 40th ICML, 23-29 July 2023 (read off the volume landing page header, not assumed), and the volume contains the title verbatim. BOTH VALUES RETAINED per the repo contract: 2022 was the previous field value and is the arXiv posting year (published 2022-12-17), which is still a true statement about the preprint. arxiv_id unchanged (2212.04356). status set to contested because this changes a published attribution.

2026-10-10: PMLR v202 ICML 2023 proceedings (idx1.py: https://proceedings.mlr.press/v202/) confirms "Robust Speech Recognition via Large-Scale Weak Supervision" (Radford et al., PMLR 202:28492-28518). arXiv API 2212.04356 (axc.py) submission verified. Source pap-mm-whisper notes cite PMLR v202:28492-28518 and PMLR v202 confirms ICML 2023 (in venue enum). Status resolved to verified.

Cross-references