Open AccessSpeech emotion recognition method based on hidden factor analysis
Author(s) -
Song Peng,
Jin Yun,
Zha Cheng,
Zhao Li
Publication year - 2015
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/el.2014.3339
Subject(s) - speech recognition , computer science , emotion recognition , factor (programming language) , pattern recognition (psychology) , artificial intelligence , programming language
A robust speech emotion recognition system relies on a large number of training data, which are difficult to collect in practice. To tackle this problem, a novel speech emotion recognition method based on hidden factor analysis is presented. By utilising the mixture of factor analysers approach, the acoustic features are decomposed into an emotion‐independent component and an emotion‐specific component. The emotion‐specific component, described by a low‐dimensional emotion identity vector, is adopted for classification. The proposed approach is evaluated via cross‐corpus emotion recognition, and the experimental results demonstrate the efficacy of the proposed method.