Speaker age identification method based on SVM (Support Vector Machine)

Abstract

The invention discloses a speaker age identification method based on an SVM (Support Vector Machine) classifier. The method comprises the following steps that a voice library in which voice signals of speakers of different ages are stored is established; the voice signals in the voice library are preprocessed; voice feature parameters of the preprocessed voice signals are extracted; the SVM training is performed on the basis of the extracted voice feature parameters, and then an SVM model is obtained; and according to the SVM model, the voice feature parameters X of voice to be identified are predicted, after output of each SVM is logically judged in the process of prediction, the voice feature parameter with the most votes is used as the most probable age class, and then a final age identification result is obtained. By using the method provided by the invention, the blank of the prior art in related research on speaker age identification is filled to a certain degree, the speaker age can be judged better, and the method has a broad application prospect on occasions such as man-machine interaction, criminal search, games, entertainments and the like.

Description

technical field [0001] The invention relates to the technical field of pattern recognition, in particular to a method for recognizing speaker age groups based on a Support Vector Machine (Support Vector Machine, SVM). Background technique [0002] At present, research technologies on speech recognition and speaker recognition are relatively mature. Other related research carried out on this basis, such as Chinese speech emotion recognition, speaker gender recognition, audio classification and recognition, etc., have also proposed corresponding solutions. However, there are few studies on the identification of the speaker's age group, but the speaker's age group identification can be applied to many occasions. Machine voice answers corresponding to age groups can increase the intimacy in human-computer interaction; or in the detection of some cases, the age group of suspects that can be identified from voice data can reduce the target search range, etc. Therefore, a method ...

AI Technical Summary

Problems solved by technology

However, there are few studies on the identification of the speaker's age group, but the speaker's age group identification can be applied to many occasions. Machine voice answers corresponding to the age group, increasing the intimacy in human-computer interaction; or in the detection of some cases, the age group of the suspect that can be identified from the voice data, reducing the target search range, etc.

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