Hu Yi, Loizou Philipos C
Department of Electrical Engineering The University of Texas at Dallas Richardson, Texas 75083-0688, USA.
Speech Commun. 2007 Jul;49(7):588-601. doi: 10.1016/j.specom.2006.12.006.
Making meaningful comparisons between the performance of the various speech enhancement algorithms proposed over the years, has been elusive due to lack of a common speech database, differences in the types of noise used and differences in the testing methodology. To facilitate such comparisons, we report on the development of a noisy speech corpus suitable for evaluation of speech enhancement algorithms. This corpus is subsequently used for the subjective evaluation of 13 speech enhancement methods encompassing four classes of algorithms: spectral subtractive, subspace, statistical-model based and Wiener-type algorithms. The subjective evaluation was performed by Dynastat, Inc. using the ITU-T P.835 methodology designed to evaluate the speech quality along three dimensions: signal distortion, noise distortion and overall quality. This paper reports the results of the subjective tests.
多年来，由于缺乏通用的语音数据库、所使用噪声类型的差异以及测试方法的不同，要对提出的各种语音增强算法的性能进行有意义的比较一直难以实现。为便于进行此类比较，我们报告了一个适用于评估语音增强算法的带噪语音语料库的开发情况。随后，该语料库被用于对涵盖四类算法（谱减法、子空间法、基于统计模型的方法和维纳型算法）的13种语音增强方法进行主观评估。主观评估由Dynastat公司采用国际电联电信标准化部门（ITU-T）P.835方法进行，该方法旨在从信号失真、噪声失真和整体质量三个维度评估语音质量。本文报告了主观测试的结果。
