标题: 具阵列拓朴向量校正之多重讯号分类演算法于即时语音处理多声源切音与分离
Real-Time Processing Of Multiple Source Segmentation and Separation Using MUSIC Algorithm with Calibrated Array Manifold Vector
作者: 叶睿诚
胡竹生
Yeh, Ruei-Cheng
Hu, Jwu-Sheng
工学院声音与音乐创意科技硕士学位学程
关键字: 校正;阵列拓朴向量;麦克风阵列;波束形成;即时语音处理;声源方位估测;array;beamforming;DOA;real-time
公开日期: 2016
摘要: 本论文提出一套即时的语音资讯处理架构,藉由校正麦克风阵列之拓朴向量(Array Manifold Vector)以后,并侦测声源方向并追踪,且实现多声源切音与分离的方法。本方法结合了多重讯号分类演算法(Multiple Signal Classification),对声源频谱及空间分布进行估测,并对频谱中可能为声源的方向进行机率决策,并利用波束形成原理将不同的方向上语音进行切音与分离。可在对多声源进行追踪并保有强健的侦测率,且可排除在声源频谱中错误侦测的声源方位。
A real-time system structure for multiple sound sources segmentation and separation using Multiple Signal Classification algorithm is proposed in this thesis. Using a calibrated array manifold vector, the proposed calibration method improves the accuracy of the MUSIC algorithm for wide-band detections, hence providing high accuracy source segmentation and separation results. And system structure using the Multiple Signal Classification algorithm to detect and estimate the localization of sound source’s spectrum distribution. And then using probability decision method to determine the direction of sound sources. Finally, multiple sources were extracted from array signals by using beamforming method. This proposed method can track and separate multiple sources at the same time and maintain high detection rate.
URI: http://etd.lib.nctu.edu.tw/cdrfb3/record/nctu/#GT070251908
http://hdl.handle.net/11536/143095
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