{"title":"Robust speaker's location estimation in a vehicle environment using GMM models","authors":"Wei-Han Liu, Chieh-Cheng Cheng, Jwusheng Hu","doi":"10.1109/IVS.2005.1505125","DOIUrl":null,"url":null,"abstract":"In this work, a robust speaker's location estimation method in a vehicle environment is presented. This method applies Gaussian mixture models (GMM) to the phase information obtained from a microphone array. The individual Gaussian component of a GMM represents some general location-dependent phase difference distribution between two microphones. These distributions are effective in modeling the speaker's location. The relation between geometry of microphone array and frequency band is taken into consideration to avoid aliasing problems. The proposed approach provides an accurate estimation even in near-field, noisy and complex vehicle environment. Moreover, it performs well not only in non-line-of-sight cases, but also in the conditions that the speakers are aligned in a direction to the microphone array with difference distances. Experiments are conducted in a mini-van vehicle and the results show that the proposed method outperform the popular technique multiple signal classification method (MUSIC) in different SNR cases.","PeriodicalId":386189,"journal":{"name":"IEEE Proceedings. Intelligent Vehicles Symposium, 2005.","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Proceedings. Intelligent Vehicles Symposium, 2005.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IVS.2005.1505125","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this work, a robust speaker's location estimation method in a vehicle environment is presented. This method applies Gaussian mixture models (GMM) to the phase information obtained from a microphone array. The individual Gaussian component of a GMM represents some general location-dependent phase difference distribution between two microphones. These distributions are effective in modeling the speaker's location. The relation between geometry of microphone array and frequency band is taken into consideration to avoid aliasing problems. The proposed approach provides an accurate estimation even in near-field, noisy and complex vehicle environment. Moreover, it performs well not only in non-line-of-sight cases, but also in the conditions that the speakers are aligned in a direction to the microphone array with difference distances. Experiments are conducted in a mini-van vehicle and the results show that the proposed method outperform the popular technique multiple signal classification method (MUSIC) in different SNR cases.