Papers

Two-channel DOA estimation usign frequency selective music algorithm with a phase compensation in reverberant room

International Conference
2006~2010
작성자
한혜원
작성일
2008-07-21 23:11
조회
4507
Authors : Jae-Mo Yang, Min-seok Choi, Hong-Goo Kang

Year : 2008

Publisher / Conference : 2008 5th IEEE Sensor Array and Multichannel Signal Processing Workshop

This paper proposes a robust two-channel frequency selective multiple signal classification (MUSIC) method to find a direction of arrival (DoA) information of speech signal. To overcome a phase distortion caused by reverberation and background noise in real acoustic room environments, we adopt a least square (LS)-based phase estimation method. In the phase compensation stage, distorted phases are replaced by estimated phases to enhance the accuracy of covariance matrix needed for the eigen-decomposition of the MUSIC method. Simulation results verify that the proposed algorithm shows much higher estimation accuracy than conventional one while its complexity can be reduced by the frequency selection method.
전체 377
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373 International Conference Jihyun Kim, Doyeon Kim, Hyewon Han, Jinyoung Lee, Jonguk Yoo, Chang Woo Han, Jeongook Song, Hoon-Young Cho, Hong-Goo Kang "Quadruple Path Modeling with Latent Feature Transfer for Permutation-free Continuous Speech Separation" in INTERSPEECH, 2025
372 International Conference Byeong Hyeon Kim,Hyungseob Lim,Inseon Jang,Hong-Goo Kang "Towards an Ultra-Low-Delay Neural Audio Coding with Computational Efficiency" in INTERSPEECH, 2025
371 International Conference Stijn Kindt,Jihyun Kim,Hong-Goo Kang,Nilesh Madhu "Efficient, Cluster-Informed, Deep Speech Separation with Cross-Cluster Information in AD-HOC Wireless Acoustic Sensor Networks" in International Workshop on Acoustic Signal Enhancement (IWAENC), 2024
370 International Conference Yeona Hong, Hyewon Han, Woo-jin Chung, Hong-Goo Kang "StableQuant: Layer Adaptive Post-Training Quantization for Speech Foundation Models" in IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2025
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