文章基本信息

标题：Speech Based Gender Identification Using Fuzzy Logic
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作者：Atif Khan ; Vikas Kumar ; Santosh Kumar 等
期刊名称：International Journal of Innovative Research in Science, Engineering and Technology
印刷版ISSN：2347-6710
电子版ISSN：2319-8753
出版年度：2017
卷号：6
期号：7
页码：14344
DOI：10.15680/IJIRSET.2017.0607242
出版社：S&S Publications
摘要：In these times one of the most important processes in speech processing is the classification of gender.Typically classification of gender is based on considering pitch as feature. The pitch value of male is lower than thefemale. In most of the topical research works the process of the classification of gender is performed using theaforementioned condition. In some cases the pitch value of female is lower and also pitch of some male is high, in thatcase the exact required result is not being produced by this classification method. By considering the aforesaid problemwe have here suggested a new method for gender classification which considers three features. In this new method thegender of the speaker is identified by using fuzzy logic. Now by using the above three features training data set isgenerated to train fuzzy logic. The performance of the proposed technique in gender classification is shown by theimplementation result.
关键词：Gender classification; fuzzy logic; power amplitude; spectrum power; total harmonic distortion