Recognition of Human Emotion from a Speech Signal Based on Plutchik's Model

Journal title

International Journal of Electronics and Telecommunications




No 2

Publication authors

Divisions of PAS

Nauki Techniczne


Polish Academy of Sciences Committee of Electronics and Telecommunications




ISSN 2081-8491 (until 2012) ; eISSN 2300-1933 (since 2013)


Plutchik R. (2001), The nature of emotion, American Scientist, 89. ; Iriea G. (2010), Affective audio-visual words and latent topic driving model for realizing movie affective scene classification, IEEE Transactions on Multimedia, 12. ; Miyakoshi Y. (null), Facial emotion detection considering partial occlusion of face using bayesian network, null. ; Z. Yang, "Multimodal datafusion for aggression detection in train compartments." February 2006. ; T. Kostoulas, T. Ganchev, and N. Fotakis, "Study on speaker-independent emotion recognition from speech on real-world data," <i>Verbal and Nonverbal Features of Human-Human and Human-Machine Interaction 2008.</i> ; Kotti M. (null), Speaker-independent negative emotion recognition, null. ; J. Cichosz and K. Ślot, "Low-dimensional feature space derivation for emotion recognition." <i>ICSES 2006.</i> ; Lugger M. (2007), The relevance of voice quality features in speaker independent emotion recognition, Proc. ICASSP. ; Z. Ciota, <i>Metody przetwarzania sygnałów akustycznych w komputerowej analizie mowy</i>, 2010, in Polish. ; T. Polzehl, A. Schmitt, and F. Metze, "Approaching multi-lingual emotion recognition from speech - on language dependency of acoustic/prosodic features for anger recognition." ; Kamaruddin N. (2010), Driver behavior analysis through speech emotion understanding, null. ; Hidayati R. (2010), The extraction of acoustic features of infant cry for emotion detection based on pitch and formants, null. ; Mower E. (2011), A framework for automatic human emotion classification using emotion profiles, Audio, Speech, and Language Processing, 19. ; Vidrascu L. (2005), Detection of real-life emotions in call centers, Proc. Eurospeech Lizbona. ; K. Izdebski, <i>Emotions in the Human Voice Volume I Foundations</i>, 2007. ; Wang Y. (2008), Recognizing human emotional state from audiovisual signals, null, 10. ; Yeqing Y. (2011), An new speech recognition method based on prosodic analysis and svm in zhuang language, null. ; Janicki A. (2008), Rozpoznawanie stanu emocjonalnego mówcy z wykorzystaniem maszyny wektor ów wspierajcych svm, null. ; Shaukat A. (2011), Emotional state recognition from speech via soft-competition on different acoustic representations, null. ; Razak A. (null), Comparison between fuzzy and nn method for speech emotion recognition, null. ; Nwe T. (2003), Detection of stress and emotion in speech using traditional and fft based log energy features, null. ; Soltani K. (2007), Speech emotion detection based on neural networks, null. ; Gaurav M. (2008), Performance analysis of spectral and prosodic features and their fusion for emotion recognition in speech, null. ; <a target="_blank" href=''></a> ; Scherer K. (2001), Emotion inferences from vocal expression correlate across languages and cultures, Journal of Cross-Cultural Psychology, 32, ; T. Zieliński, <i>Cyfrowe przetwarzanie sygnałów. Od teorii do zastosowań.</i>, October 2009., in Polish. ; <a target="_blank" href=''></a> ; Narayanan S. (2009), Analysis of emotionally salient aspects of fundamental frequency for emotion detection, IEEE Transactions on audio, speech, and language processing. ; Basztura C. (1996), Komputerowe systemy diagnostyki akustycznej. ; K. Ślot, <i>Rozpoznawanie biometryczne.</i>, December 2010, in Polish.