文章基本信息

标题：SELECTIVE NOISE FILTERING OF SPEECH SIGNALS USING AN ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM AS A FREQUENCY PRE-CLASSIFIER
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作者：SACHIN LAKRA ; T. V. PRASAD ; G. RAMAKRISHNA 等
期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2015
卷号：81
期号：3
出版社：Journal of Theoretical and Applied
摘要：The paper relates to the filtering of a noise signal present in a speech signal. Specifically, the use of an Adaptive Neuro-Fuzzy Inference System (ANFIS) to classify the frequencies present in a speech signal into three fuzzy sets, that is, those for low frequencies, voice frequencies and high frequencies is discussed in this work. Following the pre-classification step, the low frequencies are filtered which comprise the noise component in the speech signal. The pre-classifier was applied prior to the use of various FIR/IIR filters for reducing the noise present in a speech signal. The paper presents the use of an ANFIS for pre-classification of frequencies in a speech signal followed by application of a noise filter to individual or multiple classes of frequencies. It provides evidence for substantial improvement in the quality of the speech signal.
关键词：Adaptive Neuro-Fuzzy Inference Systems; Frequency pre-classifier.