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The prediction of valence from speech is an important, but challenging problem.
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2013
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C. Busso, S. Mariooryad, A. Metallinou, and S. Narayanan, “Iterative feature normalization scheme for automatic emotion detection from speech,” IEEE Transactions on Affective Computing , vol. 4, no. 4, pp. 386–397, October-December 2013
2013
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B. Schuller, S. Steidl, A. Batliner, A. Vinciarelli, K. Scherer, F. Ringeval, M. Chetouani, F. Weninger, F. Eyben, E. Marchi, M. Mortillaro, H. Salamin, A. Polychroniou, F. Valente, and S. Kim, “The INTERSPEECH 2013 computational paralinguistics challenge: Social signals, conflict, emotion, autism,” in Interspeech 2013 , Lyon, France, August 2013, pp. 148–152
2013
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J. Deng, R. Xia, Z. Zhang, Y. Liu, and B. Schuller, “Introducing shared-hidden-layer autoencoders for transfer learning and their application in acoustic emotion recognition,” in Proc. International Conference on Acoustics, Speech, and Signal Processing (ICASSP) , 2014, pp. 4851–4855
2014
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S. Mariooryad, R. Lotfian, and C. Busso, “Building a naturalistic emotional speech corpus by retrieving expressive behaviors from existing speech corpora,” in Interspeech 2014 , Singapore, September 2014, pp. 238–242
2014
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M. Abdelwahab and C. Busso, “Supervised domain adaptation for emotion recognition from speech,” in International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2015) , Brisbane, Australia, April 2015, pp. 5058–5062
2015
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G. Trigeorgis, F. Ringeval, R. Brueckner, E. Marchi, M. Nicolaou, B. Schuller, and S. Zafeiriou, “Adieu features? end-to-end speech emotion recognition using a deep convolutional recurrent network,” in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2016) , Shanghai, China, March 2016, pp. 5200–5204
2016
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P. Song, S. Ou, W. Zheng, Y. Jin, and L. Zhao, “Speech emotion recognition using transfer non-negative matrix factorization,” in Acoustics, Speech and Signal Processing (ICASSP), 2016 IEEE International Conference on . IEEE, 2016, pp. 5180–5184
2016
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Y. Zong, W. Zheng, T. Zhang, and X. Huang, “Cross-corpus speech emotion recognition based on domain-adaptive least-squares regression,” IEEE Signal Processing Letters , vol. 23, no. 5, pp. 585–589, 2016
2016
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——, “Ladder networks for emotion recognition: Using unsupervised auxiliary tasks to improve predictions of emotional attributes,” in Interspeech 2018 , Hyderabad, India, September 2018, pp. 3698–3702
2018
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K. Sridhar, S. Parthasarathy, and C. Busso, “Role of regularization in the prediction of valence from speech,” in Interspeech 2018 , Hyderabad, India, September 2018
2018
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D. Snyder, D. Garcia-Romero, G. Sell, D. Povey, and S. Khudanpur, “X-vectors: Robust dnn embeddings for speaker recognition,” in 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) . IEEE, 2018, pp. 5329–5333
2018
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J. Gideon, H. Schatten, M. McInnis, and E. Mower Provost, “Emotion recognition from natural phone conversations in individuals with and without recent suicidal ideation,” in Interspeech 2019 , Graz, Austria, September 2019, pp. 3282–3286
2019
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B. Zhang, S. Khorram, and E. Mower Provost, “Exploiting acoustic and lexical properties of phonemes to recognize valence from speech,” in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2019) , Brighton, United Kingdom, May 2019, pp. 5871–5875
2019
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E. Tournier, “Valence of emotional memories: A study of lexical and acoustic features in older adult affective speech,” Master’s thesis, Radboud University Nijmegen, Nijmegen, Netherlands, June 2019
2019
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G. Deshpande, V. S. Viraraghavan, M. Duggirala, and S. Patel, “Detecting emotional valence using time-domain analysis of speech signals,” in IEEE International Engineering in Medicine and Biology Conference (EMBC 2019) , Berlin, Germany, July 2019, pp. 3605–3608
2019
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G. Deshpande, V. Viraraghavan, and R. Gavas, “A successive difference feature for detecting emotional valence from speech,” in Workshop on Speech, Music and Mind (SMM 2019) , Vienna, Austria, September 2019, pp. 36–40
2019
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2019
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E. Lakomkin, M. Zamani, C. Weber, S. Magg, and S. Wermter, “Incorporating end-to-end speech recognition models for sentiment analysis,” in International Conference on Robotics and Automation (ICRA 2019) , Montreal, QC, Canada, May 2019, pp. 7976–7982
2019
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R. Lotfian and C. Busso, “Building naturalistic emotionally balanced speech corpus by retrieving emotional speech from existing podcast recordings,” IEEE Transactions on Affective Computing , vol. 10, no. 4, pp. 471–483, October-December 2019
2019
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