Speaker and Gender Identification on Indian Languages using Multilingual Speech
نویسندگان
چکیده
In this paper an attempt is made to develop speaker & gender identification system using continuous speech signal spoken in different languages as input. MFCCs and delta-MFCCs are used to build modal for classification . Radial basis function network is used for classification. Here resilient back propagation algorithm used to train Multilingual Speech signal . Two separate modules are used for gender and speaker identification in each experiment. In this experiment accuracy of gender identification is 98.89% and speaker recognition is 87.22% using back propagation algorithm and 99.44% and 96.11% for gender and speaker identification using radial basis function. Radial basis function network perform much better than BPA network.
منابع مشابه
Cross-lingual voice conversion-based polyglot speech synthesizer for indian languages
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