Papers by Anna Zee
Group Fairness in Multilingual Speech Recognition Models (2024.findings-naacl)
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| Challenge: | a new study evaluates the performance disparities of ASR models across languages and demographics . a large amount of data is required to mitigate performance disparity, but this is computationally expensive . |
| Approach: | They evaluate the performance disparity of ASR models using a multilingual dataset . they find that model size correlates logarithmically with worst-case performance disparities . |
| Outcome: | The proposed models exhibit significant performance disparities across binary genders for adolescents. |
On Mitigating Performance Disparities in Multilingual Speech Recognition (2024.emnlp-main)
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| Challenge: | Automatic Speech Recognition systems are not always equally effective for all users, and gender disparity in their performance is a significant concern. |
| Approach: | They compare performance of different fine-tuning algorithms for multilingual speech recognition across languages and genders. |
| Outcome: | The proposed algorithms improve performance and parity across languages and languages. |