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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2507.20926 |
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| _version_ | 1866915414718545920 |
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| author | Jing, Kangqi Zhang, Wenbin Gao, Yu |
| author_facet | Jing, Kangqi Zhang, Wenbin Gao, Yu |
| contents | Target Speaker Extraction (TSE) plays a critical role in enhancing speech signals in noisy and multi-speaker environments. This paper presents an end-to-end TSE model that incorporates Direction of Arrival (DOA) and beamwidth embeddings to extract speech from a specified spatial region centered around the DOA. Our approach efficiently captures spatial and temporal features, enabling robust performance in highly complex scenarios with multiple simultaneous speakers. Experimental results demonstrate that the proposed model not only significantly enhances the target speech within the defined beamwidth but also effectively suppresses interference from other directions, producing a clear and isolated target voice. Furthermore, the model achieves remarkable improvements in downstream Automatic Speech Recognition (ASR) tasks, making it particularly suitable for real-world applications. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2507_20926 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | End-to-End DOA-Guided Speech Extraction in Noisy Multi-Talker Scenarios Jing, Kangqi Zhang, Wenbin Gao, Yu Audio and Speech Processing Target Speaker Extraction (TSE) plays a critical role in enhancing speech signals in noisy and multi-speaker environments. This paper presents an end-to-end TSE model that incorporates Direction of Arrival (DOA) and beamwidth embeddings to extract speech from a specified spatial region centered around the DOA. Our approach efficiently captures spatial and temporal features, enabling robust performance in highly complex scenarios with multiple simultaneous speakers. Experimental results demonstrate that the proposed model not only significantly enhances the target speech within the defined beamwidth but also effectively suppresses interference from other directions, producing a clear and isolated target voice. Furthermore, the model achieves remarkable improvements in downstream Automatic Speech Recognition (ASR) tasks, making it particularly suitable for real-world applications. |
| title | End-to-End DOA-Guided Speech Extraction in Noisy Multi-Talker Scenarios |
| topic | Audio and Speech Processing |
| url | https://arxiv.org/abs/2507.20926 |