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Previously, Target Speaker Extraction (TSE) has yielded outstandingperformance in certain application scenarios for speech enhancement and sourceseparation. However, obtaining auxiliary speaker-related information is stillchallenging in noisy environments with significant reverberation. inspired bythe recently proposed distance-based sound separation, we propose the nearsound (NS) extractor, which leverages distance information for TSE to reliablyextract speaker information without requiring previous speaker enrolment,called speaker embedding self-enrollment (SESE). Full- & sub-band modeling isintroduced to enhance our NS-Extractor's adaptability towards environments withsignificant reverberation. Experimental results on several cross-datasetsdemonstrate the effectiveness of our improvements and the excellent performanceof our proposed NS-Extractor in different application scenarios.

Focus on the Sound around You: Monaural Target Speaker Extraction via Distance and Speaker Information