Papers by Paras Sharma

1 papers
Contextual ASR Error Handling with LLMs Augmentation for Goal-Oriented Conversational AI (2025.coling-industry)

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Challenge: Existing ASR correction methods rely on prior user data or named entities . Existing methods based on prior data are not available for goal-oriented dialogues .
Approach: They propose a method that integrates contextual information from the dialogue states of a goal-oriented conversational AI and its tasks into a large language model.
Outcome: The proposed method improves recall and F1 of correction by 34% and 16% while maintaining precision and false positive rate.

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