Multi-objective heuristic feature selection for speech-based multilingual emotion recognition

• Autorzy: Brester C. , Semenkin E. , Sidorov M.

Identyfikatory

DOI

10.1515/jaiscr-2016-0018

• Języki publikacji: EN

Abstrakty

EN

If conventional feature selection methods do not show sufficient effectiveness, alternative algorithmic schemes might be used. In this paper we propose an evolutionary feature selection technique based on the two-criterion optimization model. To diminish the drawbacks of genetic algorithms, which are applied as optimizers, we design a parallel multicriteria heuristic procedure based on an island model. The performance of the proposed approach was investigated on the Speech-based Emotion Recognition Problem, which reflects one of the most essential points in the sphere of human-machine communications. A number of multilingual corpora (German, English and Japanese) were involved in the experiments. According to the results obtained, a high level of emotion recognition was achieved (up to a 12.97% relative improvement compared with the best F-score value on the full set of attributes).

Słowa kluczowe

EN

multi-objective optimization; feature selection; speech-based emotion recognition

• Wydawca: University of Social Sciences
• Czasopismo: Journal of Artificial Intelligence and Soft Computing Research
• Rocznik: 2016
• Tom: Vol. 6, No. 4
• Strony: 243--253
• Opis fizyczny: Bibliogr. 20 poz., rys.

Twórcy

autor

Brester C.

• Institute of Computer Science and Telecommunications, Reshetnev Siberian State Aerospace University, Krasnoyarsky rabochy Av. 31, 660037, Krasnoyarsk, Russian Federation

autor

Semenkin E.

• Institute of Computer Science and Telecommunications, Reshetnev Siberian State Aerospace University, Krasnoyarsky rabochy Av. 31, 660037, Krasnoyarsk, Russian Federation

autor

Sidorov M.

• Institute of Communications Engineering, Ulm University, Albert EinsteinAllee 43, 89081, Ulm, Germany

Bibliografia

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Uwagi

PL

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.