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Warianty tytułu
Języki publikacji
Abstrakty
The article presents the issue of emotion recognition based on polish emotional speech analysis. 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. The following parameters extracted from sampled and normalised speech signal has been used for the analysis: energy of signal, speaker’s sex, average value of speech signal and both the minimum and maximum sample value for a given signal. As an emotional state a classifier fof our layers of artificial neural network has been used. The achieved results reach 50% of accuracy. Conducted researches focused on six emotional states: a neutral state, sadness, joy, anger, fear and boredom.
Słowa kluczowe
Wydawca
Rocznik
Tom
Strony
24--27
Opis fizyczny
Bibliogr. 16 poz., fig., tab.
Twórcy
autor
- Institute of the Foundations of Electrotechniqu and Electrotechnology, Faculty of Electric and Information Technologies, Lublin University of Technology, Nadbystrzycka 38A, 20-618 Lublin, Poland
Bibliografia
- 1. Ramakrishnan S.: Recognition of emotion from speech: A review. Speech Enhancement, Modeling and Recognition – Algorithms and Applications, March 2012.
- 2. Kamaruddin N., Wahab A.: Driver behavior analysis through speech emotion understanding. Intelligent Vehicles Symposium (IV), IEEE, 2010, 238–243.
- 3. Kamińska D., Pelikant A.: Zastosowanie multimedialnej klasyfikacji w rozpoznawaniu stanów emocjonalnych na podstawie mowy spontanicznej. IAPGOŚ 03, 2012.
- 4. Scherer K.: Vocal communication of emotions: A review of research paradigms in speech communication, 40, 2003, 227–256.
- 5. Database of Polish Emotional Speech, available: http://www.eletel.p.lodz.pl/bronakowski/med_catalog/ (Accessed 10.08.2014).
- 6. Ślot K., Rozpoznawanie biometryczne, WKiŁ, Warszawa, 2010.
- 7. Berlin Database of Emotional Speech, available: http://www.expressive-speech.net/ (Accessed 10.08.2014).
- 8. Polzehl T., Schmitt A., Metze F.: Approaching multi-lingual emotion recognition – from speech – on language dependency of acoustic/prosodic features for anger recognition. Proc. of Speech Prosody, Chicago 2010.
- 9. Yeqing Y., Tao T.: An new speech recognition method based on prosodic analysis and SVM in Zhuang language. Proc. 2011 International Conference on Mechatronic Science, Electric Engineering and Computer, 2011, 1209–1212.
- 10. Shauka A., Chen K.: Emotional state recognition from speech via soft-competition on different acoustic representations. Proc. Neural Networks (IJCNN), 2011, 1910–1917.
- 11. Plutchik R.: The nature of emotion. American Scientist, Vol. 89, July-August 2001, 344–350.
- 12. Niewiadomy D., Pelikant A.: Implementation of isolated words boundaries recognition. Proc. XII International Conference System Modeling and Control SMC, Zakopane 2006.
- 13.Janicki A., Turkot M.: Rozpoznawanie stanu emocjonalnego mówcy z wykorzystaniem maszyny wektorów wspierających (SVM). KSTiT, Bydgoszcz 2008.
- 14. Soltani K., Ainon R.: Speech emotion detection based on neural networks. Proc. Signal Processing and Its Applications, 2007, 1–3.
- 15. Zieliński T.: Cyfrowe przetwarzanie sygnałów. Od teorii do zastosowań. WKŁ 2009.
- 16. Wang Y., Guan L.: Recognizing human emotional state from audiovisual signals. Proc. IEEE Transactions on multimedia, Vol. 10, 2008, 659–668.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-4c3002ed-8220-4f01-ba87-32b1060f55d8