Recognizing emotion from Turkish speech using acoustic features

Eurasip Journal on Audio, Speech, and Music Processing

Volumn 2013, Issue 1, 2013, Pages

  Oflazoglu, Caglar ^a   Yildirim, Serdar ^a  

^a MUSTAFA KEMAL UNIVERSITY   (Turkey)

Author keywords

Cross corpus evaluation; Emotion primitives estimation; Emotion recognition; Turkish emotional speech database

Indexed keywords

CHEMICAL ACTIVATION; DATABASE SYSTEMS; SPEECH; SPEECH ANALYSIS;

AFFECTIVE COMPUTING; CROSS-CORPUS EVALUATIONS; DIMENSION ESTIMATION; EMOTION RECOGNITION; EMOTIONAL SPEECH; HUMAN MACHINE INTERACTION; RECOGNIZING EMOTIONS; TRAINING AND TESTING;

SPEECH RECOGNITION;

EID: 84893671436     PISSN: 16874714     EISSN: 16874722     Source Type: Journal    
DOI: 10.1186/1687-4722-2013-26     Document Type: Article

References (44)

1. F Burkhardt, A Paeschke, M Rolfes, W Sendlmeier, B Weiss, A database of, German emotional speech. Paper presented at the Interspeech 9th European conference on speech, communication and technology. Lisbon, Portugal, 4-8 Sept 2005
2. IS Engberg, AV Hansen, Documentation of the Danish Emotional Speech Database. (Aalborg University, Aalborg, 1996)
3. M Liberman, K Davis, M Grossman, N Martey, J Bell, Emotional Prosody, Speech and Transcripts. (Linguistic Data Consortium, Philadelphia, 2002)
4. T Banziger, M Mortillaro, K Scherer, Introducing the Geneva multimodal expression corpus for experimental research on emotion perception. Emotion. 12, 1161-1179 (2012)
5. E Douglas-Cowie, R Cowie, I Sneddon, C Cox, O Lowry, M Mcrorie, J Claude Martin, L Devillers, S Abrilian, A Batliner, N Amir, K Karpouzis, in Affective Computing and Intelligent Interaction: Lecture Notes in Computer Science, ed. by ACR Paiva, R Prada, and RW Picard. The HUMAINE Database: Addressing the collection and annotation of naturalistic and induced emotional data, vol. 4738 (Springer Berlin, 2007), pp. 488-500
6. B Schuller, B Vlasenko, F Eyben, G Rigoll, A Wendemuth, in IEEE Workshop on Automatic Speech Recognition Understanding. Acoustic emotion recognition: A benchmark comparison of performances (IEEE Merano, Italy, 13 Nov-17 Dec 2009)
7. JHL Hansen, S Bou-Ghazale, Getting started with SUSAS: A speech under simulated and actual stress database. Paper presented at the fifth European conference on speech communication and technology, EUROSPEECH 1997. Rhodes, Greece 22-25 Sept 1997
8. C Busso, M Bulut, CC Lee, A Kazemzadeh, E Mower, S Kim, J Chang, S Lee, S Narayanan, IEMOCAP: Interactive emotional dyadic motion capture database. J. Lang. Resour. Eval. 42(4), 335-359 (2008)
9. G McKeown, M Valstar, R Cowie, M Pantic, in IEEE ICME. The SEMAINE corpus of emotionally coloured character interactions (Suntec City, 19-23 Jul 2010)
10. S Steidl, Automatic Classification of Emotion Related User States in Spontaneous Children's Speech. (University of Erlangen-Nuremberg, Germany, 2009)
11. M Grimm, K Kroschel, S Narayanan, in IEEE International conference on multimedia and expo (ICME). The Vera am Mittag German audio-visual emotional speech database (IEEE Hannover, Germany, 23 Jun-26 Apr 2008)
12. C Clavel, I Vasilescu, L Devillers, T Ehrette, G Richard, in LREC. The SAFE Corpus: fear-type emotions detection for surveillance applications (Genoa, Italy, 24-26 May 2006)
13. E Douglas-Cowie, N Campbell, R Cowie, P Roach, Emotional speech: towards a new generation of databases. Speech Commun. Spec. Issue, Speech and Emotion. 40, 33-60 (2003)
14. P Ekman, in Handbook of Cognition and Emotions, ed. by L Dalgleish, M Power. Basic emotions (Wiley New York, 1999), pp. 409-589
15. E Douglas-Cowie, R Cowie, M Schroder, in ISCA Workshop on speech and emotion. A new emotion database: considerations, sources and scope (Newcastle UK, 5-7 Sept 2000)
16. J Ang, R Dhillon, A Krupski, E Shriberg, A Stolcke, in ICSLP 2002. Prosody-based automatic detection of annoyance and frustration in human-computer dialog (ISCA Denver, Colorado, 16-20 Sept 2002)
17. TL Nwe, SW Foo, L De Silva, Speech emotion recognition using hidden Markov models. Speech Commun. 41(4), 603-623 (2003)
18. CM Lee, S Narayanan, Towards detecting emotions in spoken dialogs. IEEE T Speech Audi. P. 13(2), 293-303 (2005) (Pubitemid 40320247)
19. M Grimm, K Kroschel, E Mower, S Narayanan, Primitives-based evaluation and estimation of emotions in speech. Speech Commun. 49, 787-800 (2007) (Pubitemid 47268568)
20. BS Schuller, A Batliner, D Seppi, S Steidl, T Vogt, J Wagner, L Devillers, L Vidrascu, N Amir, L Kessous, V Aharonson, in eighth conference on InterSpeech. The relevance of feature type for the automatic classification of emotional user states: low level descriptors and functionals (ISCA Antwerp, Belgium, 27-31 Aug 2007)
21. C Clavel, I Vasilescu, L Devillers, G Richard, T Ehrette, Fear-type emotion recognition for future audio-based surveillance systems. Speech Commun. 50(6), 487-503 (2008)
22. S Yildirim, S Narayanan, A Potamianos, Detecting emotional state of a child in a conversational computer game. Comput. Speech and, Lang. 25, 29-44 (2011)
23. EM Albornoz, DH Milone, HL Rufiner, Spoken emotion recognition using hierarchical classifiers. Comput. Speech and Lang. 25(3), 556-570 (2011)
24. CC Lee, E Mower, C Busso, S Lee, S Narayanan, Emotion recognition using a hierarchical binary decision tree approach. Speech Commun. 53(9-10), 1162-1171 (2011). [Special issue: Sensing Emotion and Affect - Facing Realism in Speech Processing]
25. T Polzehl, A Schmitt, F Metze, M Wagner, Anger recognition in speech using acoustic and linguistic cues. Speech Commun. 53(9-10), 1198-1209 (2011)
26. A Batliner, S Steidl, B Schuller, D Seppi, T Vogt, J Wagner, L Devillers, L Vidrascu, V Aharonson, L Kessous, N Amir, Whodunnit - searching for the most important feature types signalling emotion-related user states in speech. Comput. Speech Lang. 25, 4-28 (2011)
27. F Eyben, M Wöllmer, B Schuller, in international conference on multimedia. openSMILE: the Munich versatile and fast open-source audio feature extractor (ACM Firenze, Italy, 25-29 Oct 2010)
28. S Arunachalam, D Gould, E Andersen, D Byrd, S Narayanan, in InterSpeech. Politeness and frustration language in child-machine interactions (Aalborg Denmark, 3-7 Sept 2001)
29. A Batliner, S Steidl, B Schuller, D Seppi, K Laskowski, T Vogt, L Devillers, L Vidrascu, N Amir, L Kessous, V Aharonson, in fifth Slovenian and first international language technologies conference. Combining efforts for improving automatic classification of emotional user states (IS-LTC'06 Ljubljana, Slovenia, 9-10 Oct 2006)
30. B Schuller, A Batliner, S Steidl, D Seppi, in IEEE international conference on acoustics, speech, and signal processing. Emotion recognition from speech: putting ASR in the loop (IEEE Taipei, Taiwan, 19-24 Apr 2009)
31. B Schuller, Recognizing affect from linguistic information in 3D continuous space. IEEE Trans. Affect. Comput. 2(4), 192-205 (2012)
32. B Schuller, S Steidl, A Batliner, F Burkhardt, L Devillers, C Muller, S Narayanan, in InterSpeech. The INTERSPEECH 2010 paralinguistic challenge (Makuhari Japan, 26-30 Sept 2010)
33. M Shami, W Verhelst, in Speaker Classification II LNCS, ed. by C Müller. Automatic classification of expressiveness in speech: A multi-corpus study (Springer Berlin, 2007), pp. 43-56
34. B Schuller, B Vlasenko, F Eyben, M Wollmer, A Stuhlsatz, A Wendemuth, G Rigoll, Cross-corpus acoustic emotion recognition: variances and strategies. IEEE Trans. Affect. Comput. 1(2), 119-131 (2010)
35. C Oflazoglu, S Yildirim, in IEEE 19th conference signal processing and communications applications. Turkish emotional speech database (IEEE Antalya, Turkey, 20-22 Apr 2011)
36. J Fleiss, Measuring nominal scale agreement among many raters. Psychol. Bull. 76(5), 378-382 (1971)
37. M Bradley, PJ Lang, Measuring emotion: the self-assessment manikin and the semantic differential. J. Behav. Ther. Exp. Psychiatry. 25, 49-59 (1994) (Pubitemid 24214918)
38. M Hall, Correlation-based feature selection for machine learning. (PhD thesis, University of Waikato, New Zealand, 1999)
39. CC Chang, CJ Lin, LIBSVM: A library for support vector machines. ACM Trans. Intell. Syst. Technol. 2, 1-27 (2011)
40. MHall, E Frank, G Holmes, B Pfahringer, P Reutemann, IH Witten, The WEKA data mining software: An update. SIGKDD Explor. Newsl. 11, 10-18 (2009)
41. R Bouckaert. Bayesian Network Classifiers in Weka for Version 3-5-7, Technical Report (Waikato University Hamilton, NZ, 2008)
42. AJ Smola, B Schölkopf, A tutorial on support vector regression. Stat. Comput. 14(3), 199-222 (2004) (Pubitemid 39063488)
43. KR Scherer, R Banse, H Wallbott, Emotion inferences from vocal expression correlate across languages and cultures. J Cross Cult, Psychol. 32, 76-92 (2001)
44. M Grimm, K Kroschel, S Narayanan, in IEEE international conference on acoustics, speech and signal processing. Support vector regression for automatic recognition of spontaneous emotions in speech (Honolulu, HI, 15-20 Apr 2007)