Papers by Supriti Sinhamahapatra

2 papers
Do Slides Help? Multi-modal Context for Automatic Transcription of Conference Talks (2025.emnlp-main)

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Challenge: Current automatic speech recognition systems rely on only audio information, ignoring multi-modal context.
Approach: They propose to integrate visual context into existing automatic speech recognition systems to integrate presentation slides with multi-modal information.
Outcome: The proposed model reduces word error rate by approximately 34% across all words and 35% for domain-specific terms compared to baseline model.
How do Multimodal Foundation Models Encode Text and Speech? An Analysis of Cross-Lingual and Cross-Modal Representations (2025.naacl-short)

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Challenge: Recent advances in foundation models have sparked growing interest in expanding their text processing capabilities to speech.
Approach: They analyze the model activations from semantically equivalent sentences across languages in the text and speech modalities and examine how text and spoken are represented in recent multimodal foundation models.
Outcome: The proposed models exhibit cross-lingual differences, but are not explicitly trained for modality-agnostic representations.

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