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Speech based emotion classification

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Speech based emotion classification

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Title: Speech based emotion classification
Author: Tin, Lay Nwe; Foo, Say Wei; De Silva, Liyanage C.
Copyright year: 2001
Abstract: In this paper, a speech based emotion classification method is presented. Six basic human emotions including anger, dislike, fear, happiness, sadness and surprise are investigated. The recognizer presented in this paper is based on the discrete hidden Markov model and a novel feature vector based on mel frequency short time speech power coefficients is proposed. A universal codebook is constructed based on emotions under observation for each experiment. The databases consist of 90 emotional utterances each from two speakers. Several experiments including ungrouped emotion classification and grouped emotion classification are conducted. For the ungrouped emotion classification, an average accuracy of 72.22% and 60% are obtained respectively for utterances of the two speakers. For grouped emotion classification, higher accuracy of 94.44% and 70% are achieved
Type: Conference Paper
Conference name: International Conference on Electrical and Electronic Technology (2001)
Rights: © IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
Version: Published version

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