Digital Signal Processing Reference
In-Depth Information
78. Eyben, F., Petridis, S., Schuller, B., Pantic, M.: Audiovisual vocal outburst classification in
noisy acoustic conditions. In: Proceedings 37th IEEE International Conference on Acoustics,
Speech, and Signal Processing, ICASSP 2012, pp. 5097-5100. IEEE, Kyoto, March 2012
79. Schuller, B., Wimmer, M., Arsic, D., Rigoll, G., Radig, B.: Audiovisual behavior modeling by
combined feature spaces. In: Proceedings 32nd IEEE International Conference on Acoustics,
Speech, and Signal Processing, ICASSP 2007, vol. II, pp. 733-736. IEEE, Honolulu, April
2007
80. Schröder, M., Bevacqua, E., Eyben, F., Gunes, H., Heylen, D., ter Maat, M., Pammi, S., Pantic,
M., Pelachaud, C., Schuller, B., de Sevin, E., Valstar, M., Wöllmer, M.: A demonstration
of audiovisual sensitive artificial listeners. In: Proceedings 3rd International Conference on
Affective Computing and Intelligent Interaction and Workshops, ACII 2009, vol. I, pp. 263-
264. IEEE, Amsterdam, Sept 2009
81. Schröder, M., Bevacqua, E., Cowie, R., Eyben, F., Gunes, H., Heylen, D., ter Maat, M.,
McKeown, G., Pammi, S., Pantic, M., Pelachaud, C., Schuller, B., de Sevin, E., Valstar, M.,
Wöllmer, M.: Building autonomous sensitive artificial listeners. IEEE Trans. Affect. Comput.
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(2), 165-183 (2012)
82. Eyben, F. Wöllmer, M., Valstar, M., Gunes, H., Schuller, B., Pantic, M.: String-based audio-
visual fusion of behavioural events for the assessment of dimensional affect. In: Proceedings
International Workshop on Emotion Synthesis, Representation, and Analysis in Continuous
Space, EmoSPACE 2011, Held in Conjunction with the 9th IEEE International Conference
on Automatic Face & Gesture Recognition and Workshops, FG 2011, pp. 322-329. IEEE,
Santa Barbara, March 2011
83. Metallinou, A., Wöllmer, M., Katsamanis, A., Eyben, F., Schuller, B., Narayanan, S.: Context-
sensitive learning for enhanced audiovisual emotion classification. IEEE Trans. Affect. Com-
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84. Schuller, B., Weninger, F.: Ten recent trends in computational paralinguistics. In: Esposito,
A., Vinciarelli, A., Hoffmann, R., Müller, V.C. (eds.) 4th COST 2102 International Training
School on Cognitive Behavioural Systems. Lecture Notes on Computer Science (LNCS), p.
15. Springer, Berlin (2012)
85. Schuller, B., Zhang, Z., Weninger, F., Rigoll, G.: Using multiple databases for training in
emotion recognition: to unite or to vote? In: Proceedings INTERSPEECH 2011, 12th Annual
Conference of the International Speech Communication Association, pp. 1553-1556. ISCA,
Florence, August 2011
86. Stuhlsatz, A., Meyer, C., Eyben, F., Zielke, T., Meier, G., Schuller, B.: Deep neural net-
works for acoustic emotion recognition: Raising the benchmarks. In: Proceedings 36th IEEE
International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011, pp.
5688-5691. IEEE, Prague, May 2011
87. Schuller, B., Vlasenko, B., Eyben, F., Wöllmer, M., Stuhlsatz, A., Wendemuth, A., Rigoll,
G.: Cross-corpus acoustic emotion recognition: variances and strategies. IEEE Trans. Affect.
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(2), 119-131 (2010)
88. Eyben, F., Batliner, A., Schuller, B., Seppi, D., Steidl, S.: Cross-corpus classification of real-
istic emotions: some pilot experiments. In: Devillers, L., Schuller, B., Cowie, R., Douglas-
Cowie, E., Batliner, A. (eds.) Proceedings 3rd InternationalWorkshop on EMOTION: Corpora
for Research on Emotion and Affect, Satellite of LREC 2010, pp. 77-82. European Language
Resources Association, Valletta, May 2010
89. Jia, L., Chun, C., Jiajun, B., Mingyu, Y., Jianhua, T.: Speech emotion recognition using an
enhanced co-training algorithm. In: Proceedings of the 2007 IEEE International Conference
on Multimedia and Expo, ICME 2007, pp. 999-1002. IEEE, Beijing (2007)
90. Mahdhaoui, A., Chetouani, M.: A new approach for motherese detection using a semi-
supervised algorithm. In: Machine Learning for Signal Processing XIX: Proceedings of the
2009 IEEESignal Processing SocietyWorkshop,MLSP 2009, pp. 1-6. IEEE, Grenoble (2009)
91. Yamada, M., Sugiyama, M., Matsui, T.: Semi-supervised speaker identification under covari-
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