标题: | 具阵列拓朴向量校正之多重讯号分类演算法于多声源切音与分离 Multiple Source Segmentation and Separation Using MUSIC Algorithm with Calibrated Array Manifold Vector |
作者: | 吕孟玮 Lu, Meng-Wei 胡竹生 Hu, Jwu-Sheng 工学院声音与音乐创意科技硕士学位学程 |
关键字: | 阵列拓朴向量;多声源;分离;多重讯号分类演算法;校正;波束形成器;环状阵列;均匀环型阵列;追踪;麦克风阵列;Array Manifold Vector;Multiple Source;Separation;MUSIC Algorithm;Calibrated;Beamformer;Ring Array;Uniform Circle Array;Tracking;Microphone Array |
公开日期: | 2013 |
摘要: | 本论文提出一套利用校正过之阵列拓朴向量(Array Manifold Vector),提升多重讯号分类演算法(Multiple Signal Classification)效果在宽频估测时的准确度,并实现多声源切音与分离的方法。本方法结合了声源频谱与空间分布资讯,利用机率决策对未知数量声源方位进行分类,并将不同声源语音利用波束形成原理进行切音与分离。本方法由于进行了阵列拓朴向量的完善校正,保证在低讯噪比下对多声源的方位保有相当程度的正确率,且可排除错误侦测的声源方位。 This thesis proposes a system structure for multiple sound sources segmentation and separation using MUSIC (Multiple Signal Classification) algorithm. 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. The system structure uses a multiple signal classification algorithm to detect the location of sound sources and estimate their spectrum distributions. The multiple sources tracking method is implemented by a probability decision method regarding spatial and spectrum distributions. Using the estimated directivity, multiple sources were extracted from the array signals using beamforming methods. This proposed system structure can track and separate multiple sources at the same time and maintain high detection rate under very low SNR conditions. |
URI: | http://140.113.39.130/cdrfb3/record/nctu/#GT070051908 http://hdl.handle.net/11536/73561 |
显示于类别: | Thesis |
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