Papers by Matt Huenerfauth
A Corpus for Modeling Word Importance in Spoken Dialogue Transcripts (L18-1)
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| Challenge: | a project aims to create a system that uses automatic speech recognition (ASR) to produce real-time text captions of spoken English during in-person meetings with hearing individuals. |
| Approach: | They propose to use automatic speech recognition to produce captions in real-time . they add word-importance annotations to a transcript of a conversational dialogue corpus . |
| Outcome: | The proposed system would produce captions in real-time for people who are deaf or hard-of-hearing . the best performing model has an F-score of 0.60 in an ordinal 6-class word-importance classification task with an agreement (concordance correlation coefficient) of 0.89 with the human annotators. |
Unpacking the Interdependent Systems of Discrimination: Ableist Bias in NLP Systems through an Intersectional Lens (2021.findings-emnlp)
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| Challenge: | Statistically significant results demonstrate that people with disabilities can be disadvantaged. |
| Approach: | They used a large-scale BERT language model to predict word predictions and found that people with disabilities can be disadvantaged. |
| Outcome: | The results show that people with disabilities can be disadvantaged and that gender and race identities can be discriminated against. |