| Opensmile: the munich versatile and fast open-source audio feature extractor F Eyben, M Wöllmer, B Schuller Proceedings of the 18th ACM international conference on Multimedia, 1459-1462, 2010 | 2649 | 2010 |
| The Geneva minimalistic acoustic parameter set (GeMAPS) for voice research and affective computing F Eyben, KR Scherer, BW Schuller, J Sundberg, E André, C Busso, ... IEEE transactions on affective computing 7 (2), 190-202, 2015 | 1286 | 2015 |
| Recent developments in opensmile, the munich open-source multimedia feature extractor F Eyben, F Weninger, F Gross, B Schuller Proceedings of the 21st ACM international conference on Multimedia, 835-838, 2013 | 1261 | 2013 |
| The INTERSPEECH 2013 computational paralinguistics challenge: Social signals, conflict, emotion, autism B Schuller, S Steidl, A Batliner, A Vinciarelli, K Scherer, F Ringeval, ... Proceedings INTERSPEECH 2013, 14th Annual Conference of the International …, 2013 | 808 | 2013 |
| OpenEAR—introducing the Munich open-source emotion and affect recognition toolkit F Eyben, M Wöllmer, B Schuller 2009 3rd international conference on affective computing and intelligent …, 2009 | 504 | 2009 |
| Avec 2013: the continuous audio/visual emotion and depression recognition challenge M Valstar, B Schuller, K Smith, F Eyben, B Jiang, S Bilakhia, S Schnieder, ... Proceedings of the 3rd ACM international workshop on Audio/visual emotion …, 2013 | 500 | 2013 |
| Avec 2014: 3d dimensional affect and depression recognition challenge M Valstar, B Schuller, K Smith, T Almaev, F Eyben, J Krajewski, R Cowie, ... Proceedings of the 4th international workshop on audio/visual emotion …, 2014 | 418 | 2014 |
| Cross-corpus acoustic emotion recognition: Variances and strategies B Schuller, B Vlasenko, F Eyben, M Wöllmer, A Stuhlsatz, A Wendemuth, ... IEEE Transactions on Affective Computing 1 (2), 119-131, 2010 | 409 | 2010 |
| Abandoning emotion classes-towards continuous emotion recognition with modelling of long-range dependencies M Wöllmer, F Eyben, S Reiter, B Schuller, C Cox, E Douglas-Cowie, ... | 377 | 2008 |
| Avec 2011–the first international audio/visual emotion challenge B Schuller, M Valstar, F Eyben, G McKeown, R Cowie, M Pantic Affective Computing and Intelligent Interaction: Fourth International …, 2011 | 362 | 2011 |
| Avec 2012: the continuous audio/visual emotion challenge B Schuller, M Valster, F Eyben, R Cowie, M Pantic Proceedings of the 14th ACM international conference on Multimodal …, 2012 | 347 | 2012 |
| Acoustic emotion recognition: A benchmark comparison of performances B Schuller, B Vlasenko, F Eyben, G Rigoll, A Wendemuth 2009 IEEE Workshop on Automatic Speech Recognition & Understanding, 552-557, 2009 | 330 | 2009 |
| LSTM-Modeling of continuous emotions in an audiovisual affect recognition framework M Wöllmer, M Kaiser, F Eyben, B Schuller, G Rigoll Image and Vision Computing 31 (2), 153-163, 2013 | 313 | 2013 |
| Deep neural networks for acoustic emotion recognition: Raising the benchmarks A Stuhlsatz, C Meyer, F Eyben, T Zielke, G Meier, B Schuller 2011 IEEE international conference on acoustics, speech and signal …, 2011 | 311 | 2011 |
| The interspeech 2012 speaker trait challenge B Schuller, S Steidl, A Batliner, E Nöth, A Vinciarelli, F Burkhardt, ... INTERSPEECH 2012, Portland, OR, USA, 2012 | 305 | 2012 |
| Autoencoder-based unsupervised domain adaptation for speech emotion recognition J Deng, Z Zhang, F Eyben, B Schuller IEEE Signal Processing Letters 21 (9), 1068-1072, 2014 | 290 | 2014 |
| A novel approach for automatic acoustic novelty detection using a denoising autoencoder with bidirectional LSTM neural networks E Marchi, F Vesperini, F Eyben, S Squartini, B Schuller 2015 IEEE international conference on acoustics, speech and signal …, 2015 | 268 | 2015 |
| Real-life voice activity detection with lstm recurrent neural networks and an application to hollywood movies F Eyben, F Weninger, S Squartini, B Schuller 2013 IEEE International Conference on Acoustics, Speech and Signal …, 2013 | 268 | 2013 |
| On the acoustics of emotion in audio: what speech, music, and sound have in common F Weninger, F Eyben, BW Schuller, M Mortillaro, KR Scherer Frontiers in psychology 4, 292, 2013 | 253 | 2013 |
| Building autonomous sensitive artificial listeners M Schroder, E Bevacqua, R Cowie, F Eyben, H Gunes, D Heylen, ... IEEE transactions on affective computing 3 (2), 165-183, 2011 | 238 | 2011 |
Björn SchullerProfessor of AI, Imperial College London & University of Augsburg & CSO, audEERINGVerified email at imperial.ac.uk
