Papers by Tanvi Dinkar
The importance of fillers for text representations of speech transcripts (2020.emnlp-main)
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| Challenge: | Fillers are a type of disfluency that can be a sound ("um" or "uh") filling a pause in an utterance or conversation. |
| Approach: | They propose to represent fillers with deep contextualised embeddings to improve modelling of spoken language and two downstream tasks . |
| Outcome: | The proposed representations improve modelling of spoken language and two downstream tasks, predicting a speaker’s stance and expressed confidence. |
Mirages. On Anthropomorphism in Dialogue Systems (2023.emnlp-main)
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| Challenge: | Automated dialogue systems are anthropomorphised by developers and personified by users. |
| Approach: | They propose to examine linguistic factors that contribute to the anthropomorphism of dialogue systems and the harms that can arise thereof. |
| Outcome: | The proposed systems are anthropomorphised and personified by users . linguistic factors can also be used to reinforce gender stereotypes and conceptions of acceptable language. |
Re-examining Sexism and Misogyny Classification with Annotator Attitudes (2024.findings-emnlp)
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| Challenge: | Existing datasets for content moderation fail to capture plurality of possible annotator perspectives or ensure representation of affected groups. |
| Approach: | They examine the relationship between annotator identities and attitudes and the responses they give to two GBV labelling tasks. |
| Outcome: | The results show that higher Right Wing Authoritarianism scores are associated with a higher propensity to label text as sexist . higher scores are also associated with negative attitudes towards sexism and neosexist attitudes . |