Spectral methods in Polish emotional speech recognition
Artykuł w czasopiśmie
MNiSW
10
Lista B
| Status: | |
| Autorzy: | Powroźnik Paweł, Czerwiński Dariusz |
| Rok wydania: | 2016 |
| Wersja dokumentu: | Drukowana | Elektroniczna |
| Język: | angielski |
| Numer czasopisma: | 32 |
| Wolumen/Tom: | 10 |
| Strony: | 73 - 81 |
| Web of Science® Times Cited: | 3 |
| Bazy: | Web of Science | Directory of Open Access Journals | Index Copernicus | BazTech |
| Efekt badań statutowych | NIE |
| Materiał konferencyjny: | NIE |
| Publikacja OA: | TAK |
| Licencja: | |
| Sposób udostępnienia: | Otwarte czasopismo |
| Wersja tekstu: | Ostateczna wersja opublikowana |
| Czas opublikowania: | W momencie opublikowania |
| Data opublikowania w OA: | 1 grudnia 2016 |
| Abstrakty: | angielski |
| In this article the issue of emotion recognition based on Polish emotional speech signal analysis was presented. The Polish database of emotional speech, prepared and shared by the Medical Electronics Division of the Lodz University of Technology, has been used for research. Speech signal has been processed by Artificial Neural Networks (ANN). The inputs for ANN were information obtained from signal spectrogram. Researches were conducted for three different spectrogram divisions. The ANN consists of four layers but the number of neurons in each layer depends of spectrogram division. Conducted researches focused on six emotional states: a neutral state, sadness, joy, anger, fear and boredom. The averange effectiveness of emotions recognition was about 80%. |
