Multi-objective heuristic feature selection for speech-based multilingual emotion recognition : научное издание | Научно-инновационный портал СФУ

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

Тип публикации: статья из журнала

Год издания: 2016

Идентификатор DOI: 10.1515/jaiscr-2016-0018

Ключевые слова: feature selection, multi-objective optimization, Speech-based emotion recognition

Аннотация: 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).

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Издание

Журнал: Journal of Artificial Intelligence and Soft Computing Research

Выпуск журнала: Т. 6, 4

Номера страниц: 243-253

ISSN журнала: 20832567

Авторы

  • Brester C. (Institute of Computer Science and Telecommunications,Reshetnev Siberian State Aerospace University)
  • Semenkin E. (Institute of Computer Science and Telecommunications,Reshetnev Siberian State Aerospace University)
  • Sidorov M. (Institute of Communications Engineering,Ulm University)

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