Welcome!
Welcome to my website! I am a computer engineer, scientist, and DIY maker, combining academic, start-up, and industrial experience. Recently, I became a co-founder of a new venture (recoro.io) focusing on conversation AI. Prior to that, I conducted research in the field of multimodal and affective DL at BMW Research and for my PhD in Deep Learning at Prof. Schuller's groups. Furthermore, I am the proud founder of the MuSe-Challenge uniting worldwide research efforts to push multimodal video analysis forward.
My research and engineering projects are focused on in-the-wild (multimodal) deep learning to bring affective computing from the lab into real-world environments. This especially includes denoising in-the-wild signals and improving the robustness of such systems. Furthermore, I am interested in human-human and human-object interaction, NLP, as well as empirical and theoretical aspects of unimodal/ cross-modal representation learning. Outside of work, I spend a fair amount of time building furniture and electronic gadgets for my flat.
I am always happy to hear from like-minded people, research, and projects! Feel free to drop a line at anytime: stappen_[at]_ieee.org*
Lukas
*(remove '_' and replace at if you are not a bot)Recent Publications
L. Stappen, A. Baird, M. Lienhart, A. Bätz, B. Schuller. (2022). An Estimation of Online Video User Engagement from Features of Time- and Value-continuous, Dimensional Emotions. Frontiers in Computer Science, vol. 4.
L. Christ, S. Amiriparian, A. Baird, P. Tzirakis, A. Kathan, N. Müller, L. Stappen, et. al. (2022). The MuSe 2022 Multimodal Sentiment Analysis Challenge: Humor, Emotional Reactions, and Stress. 3rd International on Multimodal Sentiment Analysis Challenge. ACM.
I Lefter, A. Baird, L. Stappen, B. Schuller. (2022). A Cross-Corpus Speech-based Analysis of Escalating Negative Interactions. Frontiers in Computer Science.
K. Friedl, G. Rizos, L. Stappen, M. Hasan, L. Specia, T. Hain, B. Schuller. (2021). Uncertainty Aware Review Hallucination for Science Article Classification. The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021). ACL.
L. Stappen, J. Thies, G. Hagerer, B. Schuller, G. Groh. (2021). Unsupervised Graph-based Topic Modeling from Video Transcriptions. IEEE International Conference on Multimedia Big Data (BigMM), IEEE.
A. Baird, A. Triantafyllopoulos, S. Zänkert, S. Ottl, L. Christ, L. Stappen, J. Konzok, S. Sturmbauer, E.-M. Messner, B. M. Kudielka, N. Rohleder, H. Baumeister, and B. W. Schuller. (2021). An Evaluation of Speech-Based Recognition of Emotional and Physiological Markers of Stress. Frontiers in Computer Science, to appear.
L.Stappen, A. Baird, L. Christ, L. Schumann, B. Sertolli, E.-M. Messner, E. Cambria, G. Zhao, B. Schuller. (2021). The MuSe 2021 Multimodal Sentiment Analysis Challenge: Sentiment, Emotion, Physiological-Emotion, and Stress. Proceedings of the 2nd Multimodal Sentiment Analysis Challenge (MuSe). ACM.
L.Stappen, E.-M. Messner, E. Cambria, G. Zhao, B. Schuller. (2021). MuSe 2021 Challenge: Multimodal Emotion, Sentiment, Physiological-Emotion, and Stress Detection. Proceedings of the 29th ACM International Conference on Multimedia (MM '21). ACM.
L. Stappen, A. Baird, E. Cambria, B. Schuller. (2021). Sentiment Analysis and Topic Recognition in Video Transcriptions. IEEE Intelligent Systems 36(2). IEEE.
A. Baird, S. Mertes, M. Milling, L. Stappen, T. Wiest, E. André, & B. Schuller (2021). A Prototypical Network Approach for Evaluating Generated Emotional Speech. In Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH. ISCA.
L. Stappen, A. Baird, L. Schumann, B. Schuller. (2021). The Multimodal Sentiment Analysis in Car Reviews (MuSe-CaR) Dataset: Collection, Insights and Improvements. Transactions on Affective Computing (IF: 10.506 (2020), IEEE.
B. Schuller, A. Batliner, C. Bergler, C. Mascolo, J. Han, I. Lefter, H. Kaya, S. Amiriparian, A. Baird, L. Stappen, et. al.. (2021). The INTERSPEECH 2021 Computational Paralinguistics Challenge: COVID-19 cough, COVID-19 speech, escalation & primates. In Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH. ISCA.
S. Amiriparian, M. Gerczuk, S. Ottl, L. Stappen, A. Baird, et. al.. (2020). Towards cross-modal pre-training and learning tempo-spatial characteristics for audio recognition with convolutional and recurrent neural networks. EURASIP Journal on Audio, Speech, and Music Processing (1). Springer. EURASIP.
L. Stappen, B. Schuller, I. Lefter, E. Cambria, I. Kompatsiaris. (2020). Summary of MuSe 2020: Multimodal sentiment analysis, emotion-target engagement and trustworthiness detection in real-life media. In Proceedings of the 28th ACM International Conference on Multimedia (ACMMM). ACM.
L. Stappen, G. Rizos, B. Schuller. (2020). X-AWARE: ConteXt-AWARE human-environment attention fusion for driver gaze prediction in the wild. In Proceedings of the 22nd International Conference on Multimodal Interaction (ICMI). ACM.
L. Stappen, G. Rizos, M. Hasan, T. Hain, BW. Schuller. (2020). Uncertainty-Aware machine support for paper reviewing on the Interspeech 2019 Submission Corpus. In Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH. Shanghai, China. ISCA.
BW. Schuller, A. Batliner, C. Bergler, EM. Messner, A. Hamilton, S. Amiriparian, A. Baird, G. Rizos, M. Schmitt, L. Stappen et. al.. (2020). The Interspeech 2020 computational paralinguistics challenge: Elderly emotion, breathing & masks. In Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH. Shanghai, China. ISCA.
L. Stappen, A. Baird, G. Rizos, P. Tzirakis, X. Du, F. Hafner, L. Schumann, A. Mallol-Ragolta, BW. Schuller, I. Lefter, E. Cambria. (2020). MuSe 2020 challenge and workshop: Multimodal sentiment analysis, emotion-target engagement and trustworthiness detection in real-life media: Emotional car reviews in-the-wild. In Proceedings of the 1st International on Multimodal Sentiment Analysis in Real-life Media Challenge and Workshop 2020 (MuSe). ACM.
L. Stappen, X. Du, V. Karas, S. Müller, BW. Schuller. (2020). Domain Adaptation with Joint Learning for Generic, Optical Car Part Recognition and Detection Systems (Go-CaRD). under review.
ZM. Ibrahim, H. Wu, A. Hamoud, L. Stappen, RJB. Dobson, A. Agarossi. (2020). On classifying sepsis heterogeneity in the ICU: insight using machine learning. Journal of the American Medical Informatics Association 27 (3). AMIA.
L. Stappen, V. Karas, N. Cummins, F. Ringeval, K. Scherer, B. Schuller. (2019). From speech to facial activity: Towards cross-modal sequence-to-sequence attention networks. In Proceedings of the 21st IEEE International Workshop on Multimedia Signal Processing (MMSP). IEEE. - best paper award
L. Stappen, N. Cummins, EM. Meßner, H. Baumeister, J. Dineley, B. Schuller. (2019). Context modelling using hierarchical attention networks for sentiment and self-assessed emotion detection in spoken narratives. In Proceedings of the 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE.
L. Stappen, F. Brunn, B. Schuller. (2019). Cross-lingual zero-and few-shot hate speech detection utilising frozen transformer language models and AXEL. under review, preprint arXiv:2004.13850.
A. Mallol-Ragolta, Z. Zhao, L. Stappen, N. Cummins, B. Schuller. (2019). A hierarchical attention network-based approach for depression detection from transcribed clinical interviews. In Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH. ISCA.
S. Amiriparian, A. Awad, M. Gerczuk, L. Stappen, A. Baird, S. Ottl, B. Schuller. (2019). Audio-based recognition of bipolar disorder utilising capsule networks. In Proceedings of the 2019 International Joint Conference on Neural Networks (IJCNN). IEEE.