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Multimodal Data and Resource Efficient Device-Directed Speech Detection with Large Foundation Models

This paper, accepted at NeurIPS 2023, investigates removing the trigger phrase requirement from virtual assistant interactions. It proposes integrating ASR system decoder signals with acoustic and lexical inputs into a large language model to achieve more natural user communication.

 Multimodal Data and Resource Efficient Device-Directed Speech Detection with Large Foundation Models

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Embrace the future of natural user interaction with AI that understands speech without the need for a trigger phrase. Our research, featured at the Efficient Natural Language and Speech Processing workshop at NeurIPS 2023, shows the potential of enhancing virtual assistant responsiveness by integrating advanced language models with speech recognition systems.

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