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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3.6 Language Identification
- Why was Whisper weak at language identification on Fleurs?Its training data covered only 82 of Fleurs’ 102 languages, capping accuracy at 80.4%; overall it reached 64.5% vs 77.7% for the supervised state of the art.
- 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), §3.6
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