Scalogram as a representation of emotional speech
Artykuł w czasopiśmie
MNiSW
100
Lista 2021
| Status: | |
| Autorzy: | Powroźnik Paweł, Wójcicki Piotr, Przyłucki Sławomir |
| Dyscypliny: | |
| Aby zobaczyć szczegóły należy się zalogować. | |
| Rok wydania: | 2021 |
| Wersja dokumentu: | Drukowana | Elektroniczna |
| Język: | angielski |
| Wolumen/Tom: | 9 |
| Strony: | 154044 - 154057 |
| Impact Factor: | 3,476 |
| Web of Science® Times Cited: | 2 |
| Scopus® Cytowania: | 3 |
| Bazy: | Web of Science | Scopus |
| Efekt badań statutowych | NIE |
| Materiał konferencyjny: | NIE |
| Publikacja OA: | TAK |
| Licencja: | |
| Sposób udostępnienia: | Witryna wydawcy |
| Wersja tekstu: | Ostateczna wersja opublikowana |
| Czas opublikowania: | W momencie opublikowania |
| Data opublikowania w OA: | 13 listopada 2021 |
| Abstrakty: | angielski |
| It is very hard to implement the emotion recognition system based on spoken text. Computer applications have a huge problem with understanding non-literal meaning of statements as well as irony or a situational joke. The article describes how to represent emotional speech in the form of scalograms which are the result of speech signal processing by Discrete Wavelet Transform (DTW). The method of processing scalograms in order to extract input data for natural language processing algorithms in order to recognise the emotional state is also presented. The following emotional states were considered during the research: joy, anger, boredom, sadness, fear and neutral state. The developed method has been tested on databases containing recordings of emotional speech in the following languages: Polish, English, German and Danish. Depending on the language and classifier used, obtained results ranged from over 62% to over 94%. The use of fuzzy classifiers greatly improves the time and efficiency of classification. |
