Papers by Vineet Bhat

2 papers
Adversarial Training for Low-Resource Disfluency Correction (2023.findings-acl)

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Challenge: Disfluencies can be introduced in conversational speech due to the conversational nature of speech and/or speech impairments such as stuttering.
Approach: They propose an adversarial sequence-tagging model for Disfluency Correction . they evaluate it in Bengali, Hindi, and Marathi languages and use it to correct stuttering disfluencies .
Outcome: The proposed technique improves in Bengali, Hindi, and Marathi languages . it also removes stuttering disfluencies in ASR transcripts introduced by speech impairments .
DISCO: A Large Scale Human Annotated Corpus for Disfluency Correction in Indo-European Languages (2023.findings-emnlp)

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Challenge: Existing research on disfluency correction has primarily focused on English due to the unavailability of large-scale open-source datasets.
Approach: They propose to use an annotated human-annotated corpus to analyze disfluency correction in four important Indo-European languages to demonstrate the benefits.
Outcome: The proposed model improves BLEU scores by 5.65 points when used with a state-of-the-art machine translation system.

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