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The interspeech 2011 speaker state challenge
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B. Schuller, S. Steidl, A. Batliner, F. Schiel, and J. Krajewski, "The interspeech 2011 speaker state challenge," in Twelfth Annual Conference of the International Speech Communication Association, 2011.
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Twelfth Annual Conference of the International Speech Communication Association
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Avec 2011-The first international audio/visual emotion challenge
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B. Schuller, M. Valstar, F. Eyben, G. McKeown, R. Cowie, and M. Pantic, "Avec 2011-the first international audio/visual emotion challenge," Affective Computing and Intelligent Interaction, pp. 415-424, 2011.
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Recognising realistic emotions and affect in speech: State of the art and lessons learnt from the first challenge
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B. Schuller, A. Batliner, S. Steidl, and D. Seppi, "Recognising realistic emotions and affect in speech: State of the art and lessons learnt from the first challenge," Speech Communication, 2011.
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Speech Communication
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Hidden markov modelbased speech emotion recognition
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B. Schuller, G. Rigoll, and M. Lang, "Hidden markov modelbased speech emotion recognition," in Acoustics, Speech, and Signal Processing, 2003. Proceedings.(ICASSP'03). 2003 IEEE International Conference on, vol. 2. Ieee, 2003, pp. II-1.
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Frame vs. turn-level: Emotion recognition from speech considering static and dynamic processing
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B. Vlasenko, B. Schuller, A. Wendemuth, and G. Rigoll, "Frame vs. turn-level: emotion recognition from speech considering static and dynamic processing," Affective Computing and Intelligent Interaction, pp. 139-147, 2007.
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Vlasenko, B.1
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Toward detecting emotions in spoken dialogs
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C. Lee and S. Narayanan, "Toward detecting emotions in spoken dialogs," Speech and Audio Processing, IEEE Transactions on, vol. 13, no. 2, pp. 293-303, 2005.
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An i-vector extractor suitable for speaker recognition with both microphone and telephone speech
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M. Senoussaoui, P. Kenny, N. Dehak, and P. Dumouchel, "An i-vector extractor suitable for speaker recognition with both microphone and telephone speech," in Proc. Odyssey Speaker and Language Recogntion Workshop, 2010, pp. 28-33.
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Language recognition via i-vectors and dimensionality reduction
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N. Dehak, P. Torres-Carrasquillo, D. Reynolds, and R. Dehak, "Language recognition via i-vectors and dimensionality reduction," in Twelfth Annual Conference of the International Speech Communication Association, 2011.
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Application of speaker-and language identification state-of-the-art techniques for emotion recognition
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M. Kockmann, L. Burget, and J. Honza'Cernocky, "Application of speaker-and language identification state-of-the-art techniques for emotion recognition," Speech Communication, 2011.
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Speech Communication
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Speaker states recognition using latent factor analysis based eigenchannel factor vector modeling
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M. Li, A. Metallinou, D. Bone, and S. Narayanan, "Speaker states recognition using latent factor analysis based eigenchannel factor vector modeling," in Proc. of ICASSP, 2012.
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Front-end factor analysis for speaker verification
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N. Dehak, P. Kenny, R. Dehak, P. Dumouchel, and P. Ouellet, "Front-end factor analysis for speaker verification," Audio, Speech, and Language Processing, IEEE Transactions on, vol. 19, no. 4, pp. 788-798, 2011.
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Eigenvoice modeling with sparse training data
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P. Kenny, G. Boulianne, and P. Dumouchel, "Eigenvoice modeling with sparse training data," Speech and Audio Processing, IEEE Transactions on, vol. 13, no. 3, pp. 345-354, 2005.
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Analysis of emotion recognition using facial expressions, speech and multimodal information
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ACM
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C. Busso, Z. Deng, S. Yildirim, M. Bulut, C. Lee, A. Kazemzadeh, S. Lee, U. Neumann, and S. Narayanan, "Analysis of emotion recognition using facial expressions, speech and multimodal information," in Proceedings of the 6th international conference on Multimodal interfaces. ACM, 2004, pp. 205-211.
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Iemocap: Interactive emotional dyadic motion capture database
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C. Busso, M. Bulut, C. Lee, A. Kazemzadeh, E. Mower, S. Kim, J. Chang, S. Lee, and S. Narayanan, "Iemocap: Interactive emotional dyadic motion capture database," Language resources and evaluation, vol. 42, no. 4, pp. 335-359, 2008.
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Language Resources and Evaluation
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Opensmile: The Munich versatile and fast open-source audio feature extractor
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ACM
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F. Eyben, M. Wöllmer, and B. Schuller, "Opensmile: the munich versatile and fast open-source audio feature extractor," in Proceedings of the international conference on Multimedia. ACM, 2010, pp. 1459-1462.
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Proceedings of the International Conference on Multimedia
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The Interspeech 2010 paralinguistic challenge
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B. Schuller, S. Steidl, A. Batliner, F. Burkhardt, L. Devillers, C. Müller, and S. Narayanan, "The interspeech 2010 paralinguistic challenge," in Eleventh Annual Conference of the International Speech Communication Association, 2010.
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Eleventh Annual Conference of the International Speech Communication Association
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Burkhardt, F.4
Devillers, L.5
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