Robust Speech Recognition via Large-Scale Weak Supervision
Radford et al., 2023, Robust Speech Recognition via Large-Scale Weak Supervision (Proceedings of the 40th International Conference on Machine Learning (ICML 2023), PMLR 202)
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2.2 Model
- Describe Whisper’s architecture.A standard encoder–decoder Transformer, deliberately off the shelf so that results reflect the data. Audio is resampled to 16 kHz and turned into an 80-channel log-Mel spectrogram (25 ms windows, 10 ms stride) over 30-second segments; two convolution layers (the second with stride 2) precede the encoder; the decoder predicts byte-level BPE tokens.
- Radford et al., 2023, Robust Speech Recognition via Large-Scale Weak Supervision (Proceedings of the 40th International Conference on Machine Learning (ICML 2023), PMLR 202), §2.2
Source
- Alec Radford, Jong Wook Kim, Tao Xu, Greg Brockman, Christine McLeavey and Ilya Sutskever. 2023. Robust Speech Recognition via Large-Scale Weak Supervision. In Proceedings of the 40th International Conference on Machine Learning (ICML 2023), PMLR 202, pp. 28492–28518. https://proceedings.mlr.press/v202/radford23a.html