Problems of the automatic emotion recognitions in spontaneous speech; an example for the recognition in a dispatcher center

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6456 LNCS, Issue , 2011, Pages 331-339

  Vicsi, Klára ^a   Sztahó, Dávid ^a  

^a BUDAPEST UNIVERSITY OF TECHNOLOGY AND ECONOMICS   (Hungary)

Author keywords

prosodic recognizer; speech emotion database; speech emotion recognition; telephone speech

Indexed keywords

AUTOMATIC RECOGNITION SYSTEM; CONTINUOUS SPEECH; EMOTION RECOGNITION; FUNDAMENTAL FREQUENCIES; HARMONICITY; MAIN CHARACTERISTICS; PROSODIC RECOGNIZER; RECOGNITION OF EMOTION; RECOGNITION UNITS; SPECTRAL INFORMATION; SPEECH EMOTION RECOGNITION; SPONTANEOUS SPEECH; SVM CLASSIFIERS; TELECOMMUNICATION CALLS; TELEPHONE SPEECH;

DATABASE SYSTEMS; EXPERIMENTS; INTERACTIVE COMPUTER SYSTEMS; SPEECH PROCESSING; TELEPHONE; TELEPHONE SETS;

SPEECH RECOGNITION;

EID: 79952018182     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-18184-9_28     Document Type: Conference Paper

References (13)

1. Campbell, N.: Getting to the heart of the matter. Keynote Speech. In: Proc. Language resources and Evaluation Conference (LREC 2004), Lisabon, Portugal (2004)
2. Hozjan, V., Kacic, Z.: A rule-based emotion-dependent feature extraction method for emotion analysis from speech. The Journal of the Acoustical Society of America 119(5), 3109-3120 (2006)
3. Douglas-Cowie, E., Campbell, N., Cowie, R., Roach, P.: Emotional speech: towards a new generation of databases. Speech Communication 40, 33-60 (2003)
4. Burkhardt, F., Paeschke, A., et al.: A database of German Emotional Speech. In: N:Proc. of Interspeech 2005, pp. 1517-1520 (2005)
5. Navas, E., Hernáez, I., Luengo, I.: An Objective and Subjective Study of the Role of Semantics and Prosodic Features in Building Corpora for Emotional TTS. IEEE Transactions On Audio, Speech, And Language Processing 14(4) (July 2006)
6. MPEG-4: ISO/IEC 14496 standard (1999), http://www.iec.ch
7. Esposito, A.: The Perceptual and Cognitive Role of Visual and Auditory Channels in Conveying Emotional Information. In: Cogn. Comput. Springer Science+Business Media, LLC (2009), doi:10.1007/s12559-009-9017-8
8. Campbell, N: Individual Traits of Speaking Style and Speech Rhythm in a Spoken Discourse. COST Action 2102 International Conference on Verbal and Nonverbal Features.... Patras, Greece, October 2007, pp. 107-120. (2007)
9. Kostoulas, T., Ganchev, T., Fakotakis, N.: Study on Speaker-Independent Emotion Recognition from Speech on Real-World Data, COST Action 2102. In: International Conference on Verbal and Nonverbal Features, Patras, Greece, pp. 235-242 (October 2007)
10. Tóth, S.L., Sztahó, D., Vicsi, K.: Speech Emotion Perception by Human and Machine. In: Esposito, A., Bourbakis, N.G., Avouris, N., Hatzilygeroudis, I. (eds.) HH and HM Interaction. LNCS (LNAI), vol. 5042, pp. 213-224. Springer, Heidelberg (2008)
11. Vicsi, K., Szaszák, G.y.: Using Prosody for the Improvement of ASR: Sentence Modality Recognition. In: Interspeech 2008, Brisbane, Ausztrália (2008), ISCA Archive, http://www.isca-speech.org/archive (September 23-26, 2008)
12. Kohavi, R.: A study of cross-validation and bootstrap for accuracy estimation and model selection. In: Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, vol. 2(12), pp. 1137-1143 (1995)
13. Transcriber, http://trans.sourceforge.net/en/presentation.php