Speaking man recognizing method using base frequency envelope to eliminate emotion voice

Abstract

The invention relates to a speaker recognition method for filtering the emotional tone by using pitch envelop. In the test for speaker recognition, the mutually corresponding cepstrum features and pitch frequency which are firstly extracted from a segment of tone; the gender information is obtained by testing on the gender model which is trained in advance according to the cepstrum features; the thresholds adopted in the method for filtering the emotional tone are determined by gender information; the pitch envelope is picked out according to the thresholds, and then the cepstrum features are filtered according to the serial number of each frame in pitch envelope, thus acquiring the processed cepstrum features; finally, the GMM system test is carried out on the processed cepstrum features.The beneficial effects of the invention are as follows: the inconvenience to the system which needs providing the emotional tone of the speaker in the training or the emotion information of the speech in the test in a traditional method is eliminated, and the recognition performance is increased by 8% compared with traditional ASR system.

Description

technical field [0001] The invention relates to biometric feature recognition technology, and mainly relates to a speaker recognition method using fundamental frequency envelope to eliminate emotional speech. Background technique [0002] Biometric identification technology refers to a technology that uses human's own physiological or behavioral characteristics for identity authentication through computers. Based on behavioral characteristics (voice, keystroke, gait, signature, etc.), the powerful functions of computers and network technology are used for image processing and pattern recognition to identify people's identities. Voiceprint recognition or speaker recognition is one of them. It is a technology that automatically identifies the speaker's identity based on the voice parameters in the voice waveform that reflect the speaker's physiological and behavioral characteristics. [0003] Human speech contains not only text information, but also people's emotional informa...

AI Technical Summary

Problems solved by technology

In the traditional ASR (Automatic Speaker Recognition) system, the influence of the speaker's emotion is not considered, which leads to a sharp drop in the speech recognition rate of emotional differences

For how to improve the performance of the speaker recognition system under the influence of emotion, the existing methods generally need to provide the emotional speech of the test speaker during training or need to provide the emotional state information of the test speech during testing. The use of this system brings some inconvenience

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