Classification of Speech Transmission Channels:Landline,GSM and VoIP Networks

摘要：

In this paper,we study the classification of three speech transmission channels: landline telephone,mobile phone and voice over Internet protocol (VoIP),based on speech signals collected from these channels.The problem is formulated as a three-class statistical pattern classification problem.The Mel-frequency cepstral coefficients (MFCC) are used as the features for classification and the Gaussian mixture model (GMM) is used to model the distribution of the features.The maximum likelihood (ML) is used as the decision rule for the classification.Our major contribution is that we use different databases for training and testing,so the evaluation tests are completely open.In such tests,high classification accuracy around 95％ is obtained which indicates that the classification of speech transmission channels using training data is possible.We also consider factors that may influence the performance of the classification,such as the length of speech used to make a classification decision and the complexity of the GMM.

关键词： Channel classification Gaussian mixture models (GMM) Mel-frequency cepstral coefficient (MFCC) Maximum-likelihood (ML)

作者: Di Gao Xiong Xiao Guangxi Zhu Eng Siong Chng Haizhou Li

作者单位: Huazhong University of Science and Technology,Wuhan,China Nanyang Technological University,Singapore Institute for Infocomm Research (I2R),Singapore

会议类型: 国际会议

会议名称: 9th International Conference on Signal Processing(第九届国际信号处理学术会议)(ICSP08)

会议地点: 北京

会议语种:英文

在线出版日期: 2008-10-26（万方平台首次上网日期，不代表论文的发表时间）