| The INTERSPEECH 2016 Computational Paralinguistics Challenge: Deception, Sincerity & Native Language. BW Schuller, S Steidl, A Batliner, J Hirschberg, JK Burgoon, A Baird, ... INTERSPEECH, 2001-2005, 2016 | 389 | 2016 |
| Musical emotions: Predicting second-by-second subjective feelings of emotion from low-level psychoacoustic features and physiological measurements. E Coutinho, A Cangelosi Emotion 11 (4), 921, 2011 | 195 | 2011 |
| How music creates emotion: a multifactorial process approach KR Scherer, E Coutinho The Emotional Power of Music: Multidisciplinary Perspectives on Musical …, 2013 | 166 | 2013 |
| Cooperative learning and its application to emotion recognition from speech Z Zhang, E Coutinho, J Deng, B Schuller IEEE/ACM Transactions on Audio, Speech, and Language Processing 23 (1), 115-126, 2014 | 157 | 2014 |
| Psychoacoustic cues to emotion in speech prosody and music E Coutinho, N Dibben Cognition & emotion 27 (4), 658-684, 2013 | 151 | 2013 |
| Enhanced semi-supervised learning for multimodal emotion recognition Z Zhang, F Ringeval, B Dong, E Coutinho, E Marchi, B Schüller 2016 IEEE International Conference on Acoustics, Speech and Signal …, 2016 | 92 | 2016 |
| Semi-supervised active learning for sound classification in hybrid learning environments W Han, E Coutinho, H Ruan, H Li, B Schuller, X Yu, X Zhu PloS one 11 (9), e0162075, 2016 | 89 | 2016 |
| The use of spatio-temporal connectionist models in psychological studies of musical emotions E Coutinho, A Cangelosi Music Perception: An Interdisciplinary Journal 27 (1), 1-15, 2009 | 67 | 2009 |
| Connecting Subspace Learning and Extreme Learning Machine in Speech Emotion Recognition X Xu, J Deng, E Coutinho, C Wu, L Zhao, BW Schuller IEEE Transactions on Multimedia 21 (3), 795-808, 2018 | 57 | 2018 |
| Dynamic difficulty awareness training for continuous emotion prediction Z Zhang, J Han, E Coutinho, B Schuller IEEE Transactions on Multimedia 21 (5), 1289-1301, 2018 | 56 | 2018 |
| Introducing the Geneva Music-Induced Affect Checklist (GEMIAC): A brief instrument for the rapid assessment of musically induced emotions E Coutinho, KR Scherer Music Perception: An Interdisciplinary Journal 34 (4), 371-386, 2017 | 52 | 2017 |
| The effect of context and audio-visual modality on emotions elicited by a musical performance E Coutinho, KR Scherer Psychology of Music 45 (4), 550-569, 2017 | 51 | 2017 |
| Transfer learning emotion manifestation across music and speech E Coutinho, J Deng, B Schuller 2014 International Joint Conference on Neural Networks (IJCNN), 3592-3598, 2014 | 51 | 2014 |
| MUSEBAQ: A modular tool for music research to assess musicianship, musical capacity, music preferences, and motivations for music use TC Chin, E Coutinho, KR Scherer, NS Rickard Music Perception: An Interdisciplinary Journal 35 (3), 376-399, 2018 | 48 | 2018 |
| Shared acoustic codes underlie emotional communication in music and speech—Evidence from deep transfer learning E Coutinho, B Schuller PloS one 12 (6), e0179289, 2017 | 38* | 2017 |
| The Munich LSTM-RNN Approach to the MediaEval 2014 “Emotion in Music” Task E Coutinho, F Weninger, B Schuller, KR Scherer MediaEval Workshop, 5-6, 2014 | 35 | 2014 |
| Ask Alice: an artificial retrieval of information agent M Valstar, T Baur, A Cafaro, A Ghitulescu, B Potard, J Wagner, E André, ... Proceedings of the 18th ACM International Conference on Multimodal …, 2016 | 32 | 2016 |
| Automatically estimating emotion in music with deep long-short term memory recurrent neural networks E Coutinho, G Trigeorgis, S Zafeiriou, B Schuller CEUR Workshop Proceedings 1436, 1-3, 2015 | 32 | 2015 |
| Deep recurrent music writer: Memory-enhanced variational autoencoder-based musical score composition and an objective measure R Sabathé, E Coutinho, B Schuller 2017 International Joint Conference on Neural Networks (IJCNN), 3467-3474, 2017 | 26 | 2017 |
| Distributing Recognition in Computational Paralinguistics Z Zhang, E Coutinho, J Deng, B Schuller IEEE Transactions on Affective Computing 5 (4), 406-417, 2014 | 26 | 2014 |
Björn SchullerProfessor, Technische Universität München (TUM) / Imperial College London & CSO, audEERING在 tum.de 的电子邮件经过验证
