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سی و سومین کنفرانس بین المللی مهندسی برق
Single-Channel Recursive Speech Separation with Unknown Speaker Count by Mask Estimation
نویسندگان :
Hadi Alizadeh
1
Rahil Mahdian Toroghi
2
Hassan Zareian
3
1- Iran Broadcasting University
2- Iran Broadcasting University
3- Iran Broadcasting University
کلمات کلیدی :
Instantaneous Speech separation،single microphone،unknown speaker count،recursive operation،Mask estimation
چکیده :
This paper presents a novel speech separation method capable of handling an unknown number of speakers using a single, compact model, eliminating the need for prior knowledge of speaker count. The proposed approach employs a unique objective function to train a speaker-independent, single-channel model, enabling effective separation across diverse conditions, even when training and testing datasets differ. Additionally, a robust technique for detecting the number of speakers in a mixture is introduced, ensuring high performance with minimal computational complexity. By employing a recursive separation strategy, the method addresses the limitations of traditional approaches reliant on predefined speaker counts, making it more adaptable to real-world scenarios. Evaluations on the WSJ0 dataset demonstrate the proposed model's superiority in SI-SNR and SDR metrics while achieving a significantly lower parameter count compared to existing methods.
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بیشتر
ثمین همایش، سامانه مدیریت کنفرانس ها و جشنواره ها - نگارش 44.7.2
