Papers by Camille Harris
Modeling Gender and Dialect Bias in Automatic Speech Recognition (2024.findings-emnlp)
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| Challenge: | Dialect and gender-based biases have become an area of concern in language-dependent AI systems. |
| Approach: | They construct a podcast audio dataset and evaluate its performance . they then refine the models to better understand how finetuning can impact performance. |
| Outcome: | The proposed model improves on 13 hours of podcast audio transcribed by speakers of four US-based English dialects. |
VALUE: Understanding Dialect Disparity in NLU (2022.acl-long)
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| Challenge: | English Natural Language Understanding systems outperform humans on benchmarks like GLUE and SuperGLUE, but they only use textbook Standard American English (SAE) . fewer studies have considered the effects of dialectal differences on performance . |
| Approach: | They propose a benchmark to evaluate the performance of English natural language understanding systems using a set of lexical and morphosyntactic transformation rules. |
| Outcome: | The proposed model outperforms humans on GLUE and SuperGLUE, but only on standard American English . the proposed model recruits fluent speakers of African American vernacular english to validate each feature transformation . |