Papers by Akash Pandey
Can LLMs Understand Unvoiced Speech? Exploring EMG-to-Text Conversion with LLMs (2025.acl-short)
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| Challenge: | Unvoiced electromyography (EMG) is an effective communication tool for individuals unable to produce vocal speech. |
| Approach: | They propose an EMG adaptor module that maps EMG features to an LLM's input space and achieves an average word error rate of 0.49 on a closed-vocabulary unvoiced EMG-to-text task. |
| Outcome: | The proposed module achieves an average word error rate of 0.49 on a closed-vocabulary unvoiced EMG-to-text task. |
HealthAlignSumm : Utilizing Alignment for Multimodal Summarization of Code-Mixed Healthcare Dialogues (2024.findings-emnlp)
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| Challenge: | Collaboration between doctors and AI scientists is leading to personalized models to stream-line healthcare tasks and improve productivity. |
| Approach: | They propose to use alignment techniques to combine a doctor-patient dialogue with a visual component of the BART model. |
| Outcome: | The proposed model in-tegrates visual components with the BART ar-chitecture. |