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DEVELOPMENT OF EMOTION-TOLERANT INFORMATIVE INDICATORS FOR SPEECH RECOGNITION PROBLEM

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A method of the speech signal parameterization providing emotion-tolerant and speaker-invariant feature vector is proposed. The method makes use of the cepstral coefficients defined on an ExpoLog frequency scale on the base of on a linear-prediction power spectrum. The described feature vector is applied for emotional speech recognition based on hidden Markov models. Experimental results demonstrate that the use of the proposed method improves emotional speech recognition efficiency by 5,9 %.

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