Speech emotion recognition method based on spectral features and ELM

Abstract

The invention provides a speech emotion recognition method based on spectral features and ELM. The method comprises the following steps of extracting basic characteristics of an original speech signal, wherein the basic characteristics comprise rhythm characteristics and tone quality characteristics; extracting a Mel frequency cepstrum coefficient (MFCC) and a cochlear filter cepstrum coefficient(CFCC) by using a Teager energy operator TEO algorithm, weighting the MFCC and the CFCC to obtain a teCMFCC characteristic, and fusing the teCMFCC characteristic with a basic characteristic value to construct a characteristic matrix; performing selective dimension reduction on the characteristics by using a Fisher criterion and correlation analysis, and reserving the individual characteristics ofthe speech signals; and establishing an ELM decision tree model of an extreme learning machine to finish speech emotion recognition and classification. Through the method provided by the invention, the nonlinear characteristics of the speech signals are emphasized, and good robustness is provided; the test is performed on the CASIA Chinese emotion corpus recorded by the automatization institute ofChinese academy of sciences so as to verify that the proposed speech emotion recognition algorithm based on the spectral characteristics and the ELM has good classification and recognition precisionon the Chinese speech signals.

Description

technical field [0001] The present invention relates to a speech emotion recognition method, in particular to a speech emotion recognition method based on cepstral features (cepstral-based spectral feature). Background technique [0002] In 1997, Professor Picard of the Massachusetts Institute of Technology proposed the concept of Affective Computing. Affective computing, as an emerging research field interdisciplinary in computer science, neuroscience, and psychology, has become one of the important development directions of artificial intelligence. In order to understand and communicate each other's intentions in a natural way, human-computer interaction (HCI) In recent years, it has also received more and more attention, and people hope that computers can be more like people. Speech, as a fast and easy-to-understand communication method, is the most commonly used, most effective and most convenient way of communication in people's daily life. People speak through vocal c...

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During this period, it has received extensive attention from relevant researchers around the world, and has achieved some remarkable achievements, but at the same time, it is also facing the test and challenges of many problems.

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