Abstract

Emotion is one of the important factors that cause the system performance degradation. By analyzing the similarity between channel effect and emotion effect on speaker recognition, an emotion compensation method called emotion attribute projection (EAP) is proposed to alleviate the intraspeaker emotion variability. The use of this method has achieved an equal error rate (EER) reduction of 11.7% with the EER reduced from 9.81% to 8.66%. When a linear fusion based on a GMM-UBM system with an EER of 9.38% and an SVM-EAP system with an EER of 8.66% is adopted, another EER reduction of 22.5% and 16.1% can be further achieved, respectively, and the final EER can be 7.27%. Index Terms: speaker recognition, emotional speech, emotion attribute projection, fusion

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.