- Tytuł:
- Multi-objective heuristic feature selection for speech-based multilingual emotion recognition
- Autorzy:
-
Brester, C.
Semenkin, E.
Sidorov, M. - Powiązania:
- https://bibliotekanauki.pl/articles/91588.pdf
- Data publikacji:
- 2016
- Wydawca:
- Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
- Tematy:
-
multi-objective optimization
feature selection
speech-based emotion recognition - Opis:
- 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).
- Źródło:
-
Journal of Artificial Intelligence and Soft Computing Research; 2016, 6, 4; 243-253
2083-2567
2449-6499 - Pojawia się w:
- Journal of Artificial Intelligence and Soft Computing Research
- Dostawca treści:
- Biblioteka Nauki
Artykuł