Papers by Ashwani Bhat

3 papers
CISLR: Corpus for Indian Sign Language Recognition (2022.emnlp-main)

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Challenge: Existing work on natural language processing has shown promising improvements in text classification, translation and generation in widely used spoken languages.
Approach: They propose a new Indian Sign Language corpus for word-level recognition using videos . they propose CISLR model that leverages resource rich American Sign Language to learn generalized features for improving Indian Sign language predictions.
Outcome: The proposed model improves word recognition in Indian Sign Language using video . it leverages resource rich American Sign Language to learn generalized features .
Adv-OLM: Generating Textual Adversaries via OLM (2021.eacl-main)

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Challenge: Recent studies have pointed out the vulnerability of deep learning models to adversarial attacks.
Approach: They propose a black-box attack method that adapts the idea of Occlusion and Language Models to the current state of the art attack methods.
Outcome: The proposed method outperforms existing methods on several text classification tasks.
COGMEN: COntextualized GNN based Multimodal Emotion recognitioN (2022.naacl-main)

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Challenge: During a conversation, a person’s emotions are influenced by the other speaker’s utterances and their own emotional state over the utterrances.
Approach: They propose a Graph Neural Network based Multi-modal Emotion recognitioN system that leverages local and global information in a conversation.
Outcome: The proposed system gives state-of-the-art results on IEMOCAP and MOSEI datasets and detailed ablation experiments show the importance of modeling information at both levels.

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