Audio-based emotion recognition in judicial domain: A multilayer support vector machines approach

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

Volumn 5632 LNAI, Issue , 2009, Pages 594-602

  Fersini, E ^a   Messina, E ^a   Arosio, G ^a   Archetti, F ^a,b  

^a UNIVERSITY OF MILANO BICOCCA   (Italy)

^b Consorzio Milano Ricerche ^*  (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

AUDIO-BASED; CLASSIFICATION ACCURACY; CLASSIFICATION METHODS; EMOTION RECOGNITION; EMOTIONAL DATABASE; EMOTIONAL STATE; HIERARCHICAL CLASSIFICATION; HIERARCHICAL LEARNING; K-NEAREST NEIGHBORS; NAIVE BAYES; RECENT PROGRESS; RECORDING SYSTEMS; RISK MINIMIZATION; SEMANTIC RETRIEVAL;

FACE RECOGNITION; MULTIMEDIA SYSTEMS; PATTERN RECOGNITION; RISK PERCEPTION; ROBOT LEARNING; SEMANTICS; SUPPORT VECTOR MACHINES;

PSYCHOLOGY COMPUTING;

EID: 70350235187     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-03070-3_45     Document Type: Conference Paper

References (16)

1. Batliner, A., Fischer, K., Huber, R., Spilker, J., Nöth, E.: How to find trouble in communication. Speech Commun. 40(1-2), 117-143 (2003)
2. Burkhardt, F., Paeschke, A., Rolfes, M., Sendlmeier, W., Weiss, B.: A database of german emotional speech. In: Interspeech 2005, pp. 1517-1520 (2005)
3. Dellaert, F., Polzin, T., Waibel, A.: Recognizing emotion in speech. In: Proc. of the CMC, pp. 1970-1973 (1996)
4. Guyon, I., Elisseeff, A.: An introduction to variable and feature selection. J. Mach. Learn. Res. 3, 1157-1182 (2003)
5. Slot, K., Cichosz, J.: Application of selected speech-signal characteristics to emotion recognition in polish language. In: Proc. of the 5th International Conf. on signals and electronic systems, pp. 409-412 (2004)
6. Nwe, T.L., Foo, S.W., De Silva, L.C.: Speech emotion recognition using hidden markov models. Speech Communication 41(4), 603-623 (2003)
7. Petrushin, V.: Emotion recognition in speech signal: Experimental study, development, and application. In: Proc. Sixth International Conf. on Spoken Language Processing (ICSLP 2000), pp. 222-225 (2000)
8. Polzin, T., Waibel, A.: Emotion-sensitive human-computer interface. In: Proc. of the ISCA Workshop on Speech and Emotion (2000)
9. Dordevic, M., Rajkovic, M., Jovicic, S., Kasic, Z.: Serbian emotional speech database: design, processing and evaluation. In: Proc. of the 9th Conf. on Speech and Computer
10. Schuller, B., Arsic, D., Wallhoff, F., Rigoll, G.: Emotion recognition in the noise applying large acoustic feature sets. In: Speech Prosody (2006)
11. Schuller, B., Reiter, S., Rigoll, G.: Evolutionary feature generation in speech emotion recognition. In: Proceeding of the 2005 IEEE International Conf. on Multimedia and Expo., pp. 5-8 (2005)
12. Sedaaghi, M.H., Kotropoulos, C., Ververidis, D.: Using adaptive genetic algorithms to improve speech emotion recognition. In: Proc. of 9th Multimedia Signal Processing Workshop, pp. 461-464 (2007)
13. Sedaaghi, M.H., Kotropoulos, C., Ververidis, D.: Using adaptive genetic algorithms to improve speech emotion recognition. In: Proc. XV European Signal Processing Conf., pp. 2209-2213 (2007)
14. Väyrynen, E., Seppänen, T., Toivanen, J.: Automatic discrimination of emotion from spoken finish. Language and Speech 47(4), 383-412 (2004)
15. Oudeyer, P.y.: Novel useful features and algorithms for the recognition of emotions in speech. In: Proc. of the 1st International Conf. on Speech Prosody, pp. 547-550 (2002)
16. Oudeyer, P.y.: The production and recognition of emotions in speech: features and algorithms. Int. J. Hum.-Comput. Stud. 59(1-2), 157-183 (2003)