| Towards automatic airborne pollen monitoring: From commercial devices to operational by mitigating class-imbalance in a deep learning approach J Schaefer, M Milling, BW Schuller, B Bauer, JO Brunner, ... Science of the Total Environment 796, 148932, 2021 | 17 | 2021 |
| Emotion recognition in public speaking scenarios utilising an lstm-rnn approach with attention A Baird, S Amiriparian, M Milling, BW Schuller 2021 IEEE Spoken Language Technology Workshop (SLT), 397-402, 2021 | 14 | 2021 |
| Emotion and themes recognition in music utilising convolutional and recurrent neural networks S Amiriparian, M Gerczuk, E Coutinho, A Baird, S Ottl, M Milling, ... CEUR Workshop Proceedings 2670, 2019 | 12 | 2019 |
| Synchronization in interpersonal speech S Amiriparian, J Han, M Schmitt, A Baird, A Mallol-Ragolta, M Milling, ... Frontiers in Robotics and AI 6, 116, 2019 | 9 | 2019 |
| On the impact of word error rate on acoustic-linguistic speech emotion recognition: An update for the deep learning era S Amiriparian, A Sokolov, I Aslan, L Christ, M Gerczuk, T Hübner, ... arXiv preprint arXiv:2104.10121, 2021 | 5 | 2021 |
| Is speech the new blood? Recent progress in AI-based disease detection from audio in a nutshell M Milling, FB Pokorny, KD Bartl-Pokorny, BW Schuller | 4 | 2022 |
| Personalised depression forecasting using mobile sensor data and ecological momentary assessment A Kathan, M Harrer, L Küster, A Triantafyllopoulos, X He, M Milling, ... | 3 | 2022 |
| Evaluating the impact of voice activity detection on speech emotion recognition for autistic children M Milling, A Baird, KD Bartl-Pokorny, S Liu, AM Alcorn, J Shen, ... Frontiers in Computer Science 4, 1, 2022 | 3 | 2022 |
| Fairness and underspecification in acoustic scene classification: The case for disaggregated evaluations A Triantafyllopoulos, M Milling, K Drossos, BW Schuller arXiv preprint arXiv:2110.01506, 2021 | 3 | 2021 |
| Depression diagnosis and forecast based on mobile phone sensor data X He, A Triantafyllopoulos, A Kathan, M Milling, T Yan, ST Rajamani, ... 2022 44th Annual International Conference of the IEEE Engineering in …, 2022 | 2 | 2022 |
| Supervised contrastive learning for game-play frustration detection from speech M Song, E Parada-Cabaleiro, S Liu, M Milling, A Baird, Z Yang, ... Universal Access in Human-Computer Interaction. Design Methods and User …, 2021 | 2 | 2021 |
| A Prototypical Network Approach for Evaluating Generated Emotional Speech}} A Baird, S Mertes, M Milling, L Stappen, T Wiest, E André, BW Schuller Proc. Interspeech 2021, 3161-3165, 2021 | 2 | 2021 |
| Journaling data for daily PHQ-2 depression prediction and forecasting A Kathan, A Triantafyllopoulos, X He, M Milling, T Yan, ST Rajamani, ... 2022 44th Annual International Conference of the IEEE Engineering in …, 2022 | 1 | 2022 |
| Airborne pollen grain detection from partially labelled data utilising semi-supervised learning B Jin, M Milling, MP Plaza, JO Brunner, C Traidl-Hoffmann, BW Schuller, ... Science of The Total Environment, 164295, 2023 | | 2023 |
| HEAR4Health: A blueprint for making computer audition a staple of modern healthcare A Triantafyllopoulos, A Kathan, A Baird, L Christ, A Gebhard, M Gerczuk, ... arXiv preprint arXiv:2301.10477, 2023 | | 2023 |
| Automatic Emotion Modelling in Written Stories L Christ, S Amiriparian, M Milling, I Aslan, BW Schuller arXiv preprint arXiv:2212.11382, 2022 | | 2022 |
| Online Personalisation of Deep Mobile Activity Recognisers M Milling, I Aslan, M Berghofer, A Mallol-Ragolta, U Kunwar, BW Schuller Proceedings of the 7th International Workshop on Sensor-based Activity …, 2022 | | 2022 |
| Investigating Automatic Speech Emotion Recognition for Children with Autism Spectrum Disorder in interactive intervention sessions with the social robot Kaspar M Milling, KD Bartl-Pokorny, BW Schuller medRxiv, 2022.02. 24.22271443, 2022 | | 2022 |
| Stimme, das neue Blut!? Künstliche Intelligenz auf dem Weg Erkrankungen zu ‚hören ‘ M Milling, FB Pokorny, KD Bartl-Pokorny, BW Schuller Digitalisierung und Gesundheit, 113-136, 2022 | | 2022 |
| Predicting Sex and Stroke Success--Computer-aided Player Grunt Analysis in Tennis Matches L Stappen, M Milling, V Munst, K Hoffmann, BW Schuller arXiv preprint arXiv:2202.09102, 2022 | | 2022 |
Björn SchullerProfessor of AI, Imperial College London & University of Augsburg & CSO, audEERINGVerified email at imperial.ac.uk
