Simplified Deformation Compensation for Emotional Speaker Recognition

Abstract

Emotional speaker recognition has been investigated by a number of researchers, however, all the current approaches had flaws in the requirement of a large amount of emotional speech from speakers during training and even the emotional state of a user during testing, which hinder the commercialization of speaker recognition technology. We propose our method from novel view of MFCC deformation caused by pitch deviation, named pitch deviation-based cepstrum compensation (PDCC), which take into account the correlation between glottis and vocal tract. Our method is applied to two emotional speech corpus EPS and MASC with absolute IR (identification rate) increase by 10.1% for the former and 4.12% for the latter, which are promising results .