| Exploring automatic diagnosis of COVID-19 from crowdsourced respiratory sound data C Brown, J Chauhan, A Grammenos, J Han, A Hasthanasombat, ... ACM SIGKDD International Conference on Knowledge Discovery & Data Mining …, 2020 | 515 | 2020 |
| Sewa db: A rich database for audio-visual emotion and sentiment research in the wild J Kossaifi, R Walecki, Y Panagakis, J Shen, M Schmitt, F Ringeval, J Han, ... IEEE transactions on pattern analysis and machine intelligence 43 (3), 1022-1040, 2019 | 262 | 2019 |
| The INTERSPEECH 2021 Computational Paralinguistics Challenge: COVID-19 cough, COVID-19 speech, escalation & primates BW Schuller, A Batliner, C Bergler, C Mascolo, J Han, I Lefter, H Kaya, ... INTERSPEECH, 2021 | 140 | 2021 |
| An Early Study on Intelligent Analysis of Speech under COVID-19: Severity, Sleep Quality, Fatigue, and Anxiety J Han, K Qian, M Song, Z Yang, Z Ren, S Liu, J Liu, H Zheng, W Ji, ... Proc. INTERSPEECH, 4946-4950, 2020 | 130 | 2020 |
| From Hard to Soft: Towards more Human-like Emotion Recognition by Modelling the Perception Uncertainty J Han, Z Zhang, M Schmitt, M Pantic, B Schuller ACM Multimedia, 890-897, 2017 | 114 | 2017 |
| Exploring Automatic COVID-19 Diagnosis via voice and symptoms from Crowdsourced Data J Han, C Brown, J Chauhan, A Grammenos, A Hasthanasombat, ... Proc. ICASSP, 2021 | 103 | 2021 |
| Adversarial Training in Affective Computing and Sentiment Analysis: Recent Advances and Perspectives J Han, Z Zhang, N Cummins, B Schuller IEEE Computational Intelligence Magazine, 2019 | 90 | 2019 |
| Sounds of COVID-19: exploring realistic performance of audio-based digital testing J Han, T Xia, D Spathis, E Bondareva, C Brown, J Chauhan, T Dang, ... NPJ digital medicine 5 (1), 16, 2022 | 87 | 2022 |
| Learning image-based representations for heart sound classification Z Ren, N Cummins, V Pandit, J Han, K Qian, B Schuller Proceedings of the 2018 international conference on digital health, 143-147, 2018 | 86 | 2018 |
| Attention-based Atrous Convolutional Neural Networks: Visualisation AND Understanding Perspectives of Acoustic Scenes Z Ren, Q Kong, J Han, M Plumbley, BW Schuller ICASSP 2019- 2019 Proceedings IEEE International Conference on Acoustics …, 2019 | 73 | 2019 |
| COVID-19 sounds: a large-scale audio dataset for digital respiratory screening T Xia, D Spathis, J Ch, A Grammenos, J Han, A Hasthanasombat, ... Thirty-fifth conference on neural information processing systems datasets …, 2021 | 71 | 2021 |
| EmoBed: Strengthening monomodal emotion recognition via training with crossmodal emotion embeddings J Han, Z Zhang, Z Ren, B Schuller IEEE Transactions on Affective Computing 12 (3), 553-564, 2019 | 65 | 2019 |
| Facing realism in spontaneous emotion recognition from speech: Feature enhancement by autoencoder with LSTM neural networks Z Zhang, F Ringeval, J Han, J Deng, E Marchi, B Schuller Proceedings INTERSPEECH 2016, 17th Annual Conference of the International …, 2016 | 65 | 2016 |
| Prediction-based learning for continuous emotion recognition in speech J Han, Z Zhang, F Ringeval, B Schuller 2017 IEEE international conference on acoustics, speech and signal …, 2017 | 64 | 2017 |
| Dynamic Difficulty Awareness Training for Continuous Emotion Prediction Z Zhang, J Han, E Coutinho, B Schuller IEEE Transactions on Multimedia 20, 2018 | 60 | 2018 |
| Strength modelling for real-world automatic continuous affect recognition from audiovisual signals J Han, Z Zhang, N Cummins, F Ringeval, B Schuller Image and Vision Computing 65, 76-86, 2017 | 60 | 2017 |
| Snore-GANs: Improving Automatic Snore Sound Classification with Synthesised Data Z Zhang, J Han, K Qian, C Janott, Y Guo, B Schuller IEEE Journal of Biomedical and Health Informatics, 11 pages, 2019 | 59 | 2019 |
| Cross lingual speech emotion recognition using canonical correlation analysis on principal component subspace H Sagha, J Deng, M Gavryukova, J Han, B Schuller 2016 IEEE international conference on acoustics, speech and signal …, 2016 | 55 | 2016 |
| Leveraging Unlabelled Data for Emotion Recognition with Enhanced Collaborative Semi-Supervised Learning Z Zhang, J Han, J Deng, X Xu, F Ringeval, B Schuller IEEE Access 6, 22196-22209, 2018 | 49 | 2018 |
| Reconstruction-error-based learning for continuous emotion recognition in speech J Han, Z Zhang, F Ringeval, B Schuller 2017 IEEE international conference on acoustics, speech and signal …, 2017 | 49 | 2017 |
Björn SchullerProfessor, Technische Universität München (TUM) / Imperial College London & CSO, audEERINGVerified email at tum.de
