Estimation of the Multiple Sound Source Locations Using a Microphone Array
碩士 === 國立高雄應用科技大學 === 電機工程系博碩士班 === 102 === In this thesis, we use a microphone array with blind source separation algorithm and time difference of arrival (TDOA) in far-situation to do multiple sound source localization and source number estimation. Most of the researches of multiple sound source l...
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ndltd-TW-102KUAS04420502016-03-11T04:12:50Z http://ndltd.ncl.edu.tw/handle/39874458413941779293 Estimation of the Multiple Sound Source Locations Using a Microphone Array 利用陣列式麥克風進行多聲源之定位 Yu-Ting Chen 陳右庭 碩士 國立高雄應用科技大學 電機工程系博碩士班 102 In this thesis, we use a microphone array with blind source separation algorithm and time difference of arrival (TDOA) in far-situation to do multiple sound source localization and source number estimation. Most of the researches of multiple sound source localization are focused on the angle of source. However, there is a problem that the user cannot identify the corresponding angle of each sound source, and we name this problem as data association. To solve this problem, we use nonnegative matrix factor 2-D deconvolution (NMF2D) to separate the mixed single and then we can consider the multiple sound source localization as many independent sound sources localization. Therefore, we can calculate the corresponding angle of each sound source. We also use the interaural level difference (ILD) and TDOA to estimate the distance of each sound source. Finally, the multiple sound source localization system is programmed by LabVIEW 2012 software. Luke K. Wang 王冠智 2014 學位論文 ; thesis 60 en_US |
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碩士 === 國立高雄應用科技大學 === 電機工程系博碩士班 === 102 === In this thesis, we use a microphone array with blind source separation algorithm and time difference of arrival (TDOA) in far-situation to do multiple sound source localization and source number estimation. Most of the researches of multiple sound source localization are focused on the angle of source. However, there is a problem that the user cannot identify the corresponding angle of each sound source, and we name this problem as data association. To solve this problem, we use nonnegative matrix factor 2-D deconvolution (NMF2D) to separate the mixed single and then we can consider the multiple sound source localization as many independent sound sources localization. Therefore, we can calculate the corresponding angle of each sound source. We also use the interaural level difference (ILD) and TDOA to estimate the distance of each sound source. Finally, the multiple sound source localization system is programmed by LabVIEW 2012 software.
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author2 |
Luke K. Wang |
author_facet |
Luke K. Wang Yu-Ting Chen 陳右庭 |
author |
Yu-Ting Chen 陳右庭 |
spellingShingle |
Yu-Ting Chen 陳右庭 Estimation of the Multiple Sound Source Locations Using a Microphone Array |
author_sort |
Yu-Ting Chen |
title |
Estimation of the Multiple Sound Source Locations Using a Microphone Array |
title_short |
Estimation of the Multiple Sound Source Locations Using a Microphone Array |
title_full |
Estimation of the Multiple Sound Source Locations Using a Microphone Array |
title_fullStr |
Estimation of the Multiple Sound Source Locations Using a Microphone Array |
title_full_unstemmed |
Estimation of the Multiple Sound Source Locations Using a Microphone Array |
title_sort |
estimation of the multiple sound source locations using a microphone array |
publishDate |
2014 |
url |
http://ndltd.ncl.edu.tw/handle/39874458413941779293 |
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