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  • 标题:Gender Classification in Speech Recognition using Fuzzy Logic and Neural Network
  • 本地全文:下载
  • 作者:Kunjithapatham Meena ; Kulumani Subramaniam ; Muthusamy Gomathy
  • 期刊名称:The International Arab Journal of Information Technology
  • 印刷版ISSN:1683-3198
  • 出版年度:2013
  • 卷号:10
  • 期号:5
  • 出版社:Zarqa Private University
  • 摘要:Nowadays classification of gender is one of the most important processes in speech processing. Usually gender classification is based on considering pitch as feature. The pitch value of female is higher than the male. In most of the recent research works gender classification process is performed using the abovementioned condition. In some cases the pitch value of male is higher and also pitch of some female is low, in that case this classification does not produce the exact required result. By considering the aforementioned problem we have here proposed a new method for gender classification method which considers three features. The new method uses fuzzy logic and neural network to identify the gender of the speaker. To train fuzzy logic and neural network, training dataset is generated by using the above three features. Then mean value is calculated for the obtained result from fuzzy logic and neural network. By using this threshold value, the proposed method identifies the speaker belongs to which gender. The implementation result shows the performance of the proposed technique in gender classification
  • 关键词:Gender classification; fuzzy logic; neural network; energy entropy; short time energy; zero crossing rate
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