Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Objective Speech Quality Measurement Using Statistical Data Mining | EURASIP Journal on Applied Signal Processing 2005 9 1410-1424 2005 Hindawi Publishing Corporation Objective Speech Quality Measurement Using Statistical Data Mining Wei Zha Power Acquisition and Telemetry Group Schlumberger Technology Corporation 150 Gillingham Lane MD 1 Sugar Land TX 77478 USA Email wzha@ Wai-Yip Chan Department of Electrical Computer Engineering Queen s University Kingston ON Canada K7L3N6 Email chan@ Received 7 November 2003 Revised 3 September 2004 Measuring speech quality by machines overcomes two major drawbacks of subjective listening tests their low speed and high cost. Real-time accurate and economical objective measurement of speech quality opens up a wide range of applications that cannot be supported with subjective listening tests. In this paper we propose a statistical data mining approach to design objective speech quality measurement algorithms. A large pool of perceptual distortion features is extracted from the speech signal. We examine using classification and regression trees CART and multivariate adaptive regression splines MARS separately and jointly to select the most salient features from the pool and to construct good estimators of subjective listening quality based on the selected features. We show designs that use perceptually significant features and outperform the state-of-the-art objective measurement algorithm. The designed algorithms are computationally simple making them suitable for real-time implementation. The proposed design method is scalable with the amount of learning data thus performance can be improved with more offline or online training. Keywords and phrases speech quality speech perception mean opinion scores data mining classification trees regression. 1. INTRODUCTION Plain old telephone service as traditionally provided using dedicated circuit-switched networks is reliable and economical. A contemporary challenge is to provide high-quality reliable and low-cost voice .
