臺灣博碩士論文加值系統

本論文提出一套即時的語音資訊處理架構，藉由校正麥克風陣列之拓樸向量(Array Manifold Vector)以後，並偵測聲源方向並追蹤，且實現多聲源切音與分離的方法。本方法結合了多重訊號分類演算法(Multiple Signal Classification)，對聲源頻譜及空間分佈進行估測，並對頻譜中可能為聲源的方向進行機率決策，並利用波束形成原理將不同的方向上語音進行切音與分離。可在對多聲源進行追蹤並保有強健的偵測率，且可排除在聲源頻譜中錯誤偵測的聲源方位。

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.

摘 要..................................................I
ABSTRACT ............................................. II
誌 謝................................................III
目　錄.................................................IV
表 列..................................................VI
圖 列.................................................VII
第一章 緒論 .............................................1
1.1 研究動機 ............................................1
1.2 研究目標.............................................1
1.3 文獻回顧.............................................2
1.4 論文架構.............................................4
第二章 背景技術介紹.......................................5
2.1 麥克風陣列訊號處理....................................5
2.2 訊號到達角度估測(DOA) ................................8
2.2.1 Multiple Signals Classification Method(MUSIC).....8
2.2.2 未知數量寬頻訊號的訊號來源角度估測...................11
2.3 利用機率模型進行聲源角度決策….........................14
2.4 使用波束形成器進行聲源切音與分離......................14
2.4.1 Least Square Solution............................15
2.4.2 Linearly Constrained Minimum-Variance Beamformer.16
2.4.3 Minimum Variance Distortionless Response Beamfor.17
2.5 陣列拓樸向量校正.....................................18
第三章 系統架構與實作....................................20
3.1 系統架構說明….......................................20
3.2 陣列拓樸向量校正.....................................21
3.2.1 雙麥克風校正......................................21
3.2.2 陣列拓樸向量校正...................................22
3.3 主要聲源方位估測與特徵值分解的聲源分離.................25
3.4 多聲源方位追蹤演算法.................................27
3.5 利用波束形成器之多聲源切音與分離......................30
3.5.1 Minimum Variance Distortionless Response Beamfor.30
第四章 實驗結果與分析....................................33
4.1 陣列拓樸向量校正結果.................................37
4.1.1 校正陣列拓樸向量對波束形成器的影響與結果.............37
4.1.2 校正陣列拓樸向量對DOA的影響與結果...................39
4.2 多聲源語音分離表現及結果..............................42
第五章 結論.............................................52
5.1 研究成果............................................52
5.2 未來展望............................................52
REFERENCE..............................................53

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