Multi-Channel Multi-Speaker ASR Using Target Speaker's Solo Segment
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arXiv
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| Autori principali: | , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866911921541742592 |
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| author | Shao, Yiwen Zhang, Shi-Xiong Xu, Yong Yu, Meng Yu, Dong Povey, Daniel Khudanpur, Sanjeev |
| author_facet | Shao, Yiwen Zhang, Shi-Xiong Xu, Yong Yu, Meng Yu, Dong Povey, Daniel Khudanpur, Sanjeev |
| contents | In the field of multi-channel, multi-speaker Automatic Speech Recognition (ASR), the task of discerning and accurately transcribing a target speaker's speech within background noise remains a formidable challenge. Traditional approaches often rely on microphone array configurations and the information of the target speaker's location or voiceprint. This study introduces the Solo Spatial Feature (Solo-SF), an innovative method that utilizes a target speaker's isolated speech segment to enhance ASR performance, thereby circumventing the need for conventional inputs like microphone array layouts. We explore effective strategies for selecting optimal solo segments, a crucial aspect for Solo-SF's success. Through evaluations conducted on the AliMeeting dataset and AISHELL-1 simulations, Solo-SF demonstrates superior performance over existing techniques, significantly lowering Character Error Rates (CER) in various test conditions. Our findings highlight Solo-SF's potential as an effective solution for addressing the complexities of multi-channel, multi-speaker ASR tasks. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_09589 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Multi-Channel Multi-Speaker ASR Using Target Speaker's Solo Segment Shao, Yiwen Zhang, Shi-Xiong Xu, Yong Yu, Meng Yu, Dong Povey, Daniel Khudanpur, Sanjeev Audio and Speech Processing In the field of multi-channel, multi-speaker Automatic Speech Recognition (ASR), the task of discerning and accurately transcribing a target speaker's speech within background noise remains a formidable challenge. Traditional approaches often rely on microphone array configurations and the information of the target speaker's location or voiceprint. This study introduces the Solo Spatial Feature (Solo-SF), an innovative method that utilizes a target speaker's isolated speech segment to enhance ASR performance, thereby circumventing the need for conventional inputs like microphone array layouts. We explore effective strategies for selecting optimal solo segments, a crucial aspect for Solo-SF's success. Through evaluations conducted on the AliMeeting dataset and AISHELL-1 simulations, Solo-SF demonstrates superior performance over existing techniques, significantly lowering Character Error Rates (CER) in various test conditions. Our findings highlight Solo-SF's potential as an effective solution for addressing the complexities of multi-channel, multi-speaker ASR tasks. |
| title | Multi-Channel Multi-Speaker ASR Using Target Speaker's Solo Segment |
| topic | Audio and Speech Processing |
| url | https://arxiv.org/abs/2406.09589 |