Comparison of Speaker Dependent And Speaker Independent Emotion Recognition

Jan Rybka , Artur Janicki


This paper describes a study of emotion recognition based on speech analysis. The introduction to the theory contains a review of emotion inventories used in various studies of emotion recognition as well as the speech corpora applied, methods of speech parametrization, and the most commonly employed classification algorithms. In the current study the EMO-DB speech corpus and three selected classifiers, the k-Nearest Neighbor (k-NN), the Artificial Neural Network (ANN) and Support Vector Machines (SVMs), were used in experiments. SVMs turned out to provide the best classification accuracy of 75.44% in the speaker dependent mode, that is, when speech samples from the same speaker were included in the training corpus. Various speaker dependent and speaker independent configurations were analyzed and compared. Emotion recognition in speaker dependent conditions usually yielded higher accuracy results than a similar but speaker independent configuration. The improvement was especially well observed if the base recognition ratio of a given speaker was low. Happiness and anger, as well as boredom and neutrality, proved to be the pairs of emotions most often confused.
Author Jan Rybka (FEIT / IN)
Jan Rybka,,
- The Institute of Computer Science
, Artur Janicki (FEIT / IT)
Artur Janicki,,
- The Institute of Telecommunications
Journal seriesInternational Journal of Applied Mathematics & Computer Science, [2083-8492], ISSN 1641-876X
Issue year2013
Keywords in Polishprzetwarzanie mowy, rozpoznawanie emocji, EMO-DB, sztuczne sieci neuronowe
Keywords in Englishspeech processing, emotion recognition, EMO-DB, support vector machines, artificial neural networks
ASJC Classification2604 Applied Mathematics; 2201 Engineering (miscellaneous); 1701 Computer Science (miscellaneous)
ProjectThe Develpment of Digital Communicatios. Project leader: Lubacz Józef, , Phone: 22 234 65 31, start date 04-05-2012, planned end date 31-03-2013, end date 31-12-2013, IT/2012/statut, Completed
WEiTI Działalność statutowa
Languageen angielski
Rybka, Janicki, Comparison of speaker-dependent and speaker ind., AMCS 2013.pdf 329.23 KB
Score (nominal)25
Score sourcejournalList
ScoreMinisterial score = 25.0, 02-02-2020, ArticleFromJournal
Ministerial score (2013-2016) = 25.0, 02-02-2020, ArticleFromJournal
Publication indicators WoS Citations = 10; Scopus Citations = 14; GS Citations = 19.0; Scopus SNIP (Source Normalised Impact per Paper): 2013 = 1.588; WoS Impact Factor: 2013 = 1.39 (2) - 2013=1.317 (5)
Citation count*21 (2020-09-02)
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