Papers by Amruta Parulekar
AMPS: ASR with Multimodal Paraphrase Supervision (2025.naacl-short)
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| Challenge: | Spontaneous or conversational multilingual speech presents many challenges for state-of-the-art automatic speech recognition systems. |
| Approach: | They propose a technique that augments a multilingual multimodal ASR system with paraphrase-based supervision for improved conversational ASR in multiple languages. |
| Outcome: | The proposed technique reduces word error rates by up to 5% on a state-of-the-art multimodal model . |
LASER: An LLM-based ASR Scoring and Evaluation Rubric (2025.emnlp-main)
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| Challenge: | Standard ASR evaluation metrics like word error rate penalize morphological and syntactic nuances that do not significantly alter sentence semantics. |
| Approach: | They propose an LLM-based scoring rubric LASER that leverages state-of-the-art LLMs’ in-context learning abilities to learn from prompts with detailed examples. |
| Outcome: | The proposed scoring rubric combines state-of-the-art learning capabilities with a high correlation score with human annotations. |