Two-pass Endpoint Detection for Speech Recognition

Fuente: arXiv
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Autores principales: Raju, Anirudh, Khare, Aparna, He, Di, Sklyar, Ilya, Chen, Long, Alptekin, Sam, Trinh, Viet Anh, Zhang, Zhe, Vaz, Colin, Ravichandran, Venkatesh, Maas, Roland, Rastrow, Ariya
Formato: Preprint
Publicado: 2024
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author Raju, Anirudh
Khare, Aparna
He, Di
Sklyar, Ilya
Chen, Long
Alptekin, Sam
Trinh, Viet Anh
Zhang, Zhe
Vaz, Colin
Ravichandran, Venkatesh
Maas, Roland
Rastrow, Ariya
author_facet Raju, Anirudh
Khare, Aparna
He, Di
Sklyar, Ilya
Chen, Long
Alptekin, Sam
Trinh, Viet Anh
Zhang, Zhe
Vaz, Colin
Ravichandran, Venkatesh
Maas, Roland
Rastrow, Ariya
contents Endpoint (EP) detection is a key component of far-field speech recognition systems that assist the user through voice commands. The endpoint detector has to trade-off between accuracy and latency, since waiting longer reduces the cases of users being cut-off early. We propose a novel two-pass solution for endpointing, where the utterance endpoint detected from a first pass endpointer is verified by a 2nd-pass model termed EP Arbitrator. Our method improves the trade-off between early cut-offs and latency over a baseline endpointer, as tested on datasets including voice-assistant transactional queries, conversational speech, and the public SLURP corpus. We demonstrate that our method shows improvements regardless of the first-pass EP model used.
format Preprint
id arxiv_https___arxiv_org_abs_2401_08916
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Two-pass Endpoint Detection for Speech Recognition
Raju, Anirudh
Khare, Aparna
He, Di
Sklyar, Ilya
Chen, Long
Alptekin, Sam
Trinh, Viet Anh
Zhang, Zhe
Vaz, Colin
Ravichandran, Venkatesh
Maas, Roland
Rastrow, Ariya
Audio and Speech Processing
Sound
Endpoint (EP) detection is a key component of far-field speech recognition systems that assist the user through voice commands. The endpoint detector has to trade-off between accuracy and latency, since waiting longer reduces the cases of users being cut-off early. We propose a novel two-pass solution for endpointing, where the utterance endpoint detected from a first pass endpointer is verified by a 2nd-pass model termed EP Arbitrator. Our method improves the trade-off between early cut-offs and latency over a baseline endpointer, as tested on datasets including voice-assistant transactional queries, conversational speech, and the public SLURP corpus. We demonstrate that our method shows improvements regardless of the first-pass EP model used.
title Two-pass Endpoint Detection for Speech Recognition
topic Audio and Speech Processing
Sound
url https://arxiv.org/abs/2401.08916