Lehrstuhl für Embedded Intelligence for Health Care and Wellbeing

  1. Universität
  2. Fakultäten
  3. Fakultät für Angewandte Informatik
  4. Institut für Informatik
  5. Lehrstühle und Professuren der Informatik
  6. Embedded Intelligence for Health Care and Wellbeing
  7. Forschung
  8. Publikationen

Publikationen

Book Chapters

2022

  • B. W. Schuller, P. N. Pham, S. Do, C. S. Pattichis, and P. Nair, eds., Health Technologies and Innovations to Effectively Respond to the COVID-19 Pandemic. Frontiers in Digital Health, Frontiers Media, 1 ed., 2 2022. 197 pages

2021

  • F. Pokorny and B. Schuller, “Perspectives of Sound Engineering,” in Oxford Handbook of Language and Music (D. Sammler, ed.), Oxford University Press, 2021. invited, to appear
  • V.Karas and B. W. Schuller. "Deep learning for sentiment analysis: an overview and perspectives." Natural Language Processing for Global and Local Business (F. Pinarbasi and M. N. Taskiran), IGI Global, 2021: 97-132.
  • M. Milling, F. B. Pokorny, K. D. Bartl-Pokorny and B. W. Schuller. „Stimme, das neue Blut!? Künstliche Intelligenz auf dem Weg Erkrankungen zu hören“. Technik und Gesundheit (U. Gassner), Nomos. 18 pages, to appear.

 

2019

  • A. Batliner and B. Möbius, "Prosody in Automatic Speech Processing," in The Oxford Handbook of Language Prosody (C. Gussenhoven and Aoju Chen, eds.), Oxford University Press. 20 pages, 2019. PDF

Journal Papers

2022

  • S. Liu, A. Mallol-Ragolta, T. Yan, K. Qian, E. ParadaCabaleiro, B. Hu, and B. W. Schuller, “Capturing Time Dynamics from Speech using Neural Networks for Surgical Masks Detection,” IEEE Journal of Biomedical and Health Informatics, vol. 26, 2022. 14 pages, to appear (IF: 5.772 (2021))

  • S. Ottl, S. Amiriparian, M. Gerczuka, and B. W. Schuller, “motilitAI: A Machine Learning Framework for Automatic Prediction of Human Semen Motility,” iScience, 2022. 13 pages, to appear

  • F. B. Pokorny, M. Schmitt, M. Egger, K. D. BartlPokorny, D. Zhang, B. W. Schuller, and P. B. Marschik, “Automatic vocalisation-based detection of fragile X syndrome and Rett syndrome,” Scientific Reports, vol. 12, 2022. 16 pages, to appear (IF: 4.996 (2021))

  • L. Stappen, A. Baird, M. Lienhart, A. Bätz, and B. W. Schuller, “An Estimation of Online Video User Engagement from Features of Time- and Value-continuous, Dimensional Emotions,” Frontiers in Computer Science, section Human-Media Interaction, vol. 4, 2022. 13 pages, to appear

  • B. Schuller, A. Baird, A. Gebhard, S. Amiriparian, G. Keren, M. Schmitt, and N. Cummins, “New Avenues in Audio Intelligence: Towards Holistic Real-life Audio Understanding,” Trends in Hearing, vol. 25, pp. 1–14, 11 2021. (IF: 3.293 (2020)) open access

  • L. Stappen, A. Baird, M. Lienhart, A. Bätz, and B. W. Schuller, “An Estimation of Online Video User Engagement from Features of Time- and Value-continuous, Dimensional Emotions,” Frontiers in Computer Science, section Human-Media Interaction, vol. 4, 2022. 13 pages, to appear

  • M. Milling, A. Baird, K. D. Bartl-Pokorny, S. Liu, A. M. Alcorn, J. Shen, T. Tavassoli, E. Ainger, E. Pellicano, M. Pantic, N. Cummins, and B. W. Schuller, “Evaluating the Impact of Voice Activity Detection on Speech Emotion Recognition for Autistic Children,” Frontiers in Computer Science, section Human-Media Interaction, vol. 4, 2022. 12 pages, to appear open access

  • A. Mallol-Ragolta, A. Semertzidou, M. Pateraki, and B. Schuller, “Outer Product-based Fusion of Smartwatch Sensor Data for Human Activity Recognition,” Frontiers in Computer Science, section Mobile and Ubiquitous Computing, vol. 4, 2022. 15 pages, to appear

  • K. D. Bartl-Pokorny, F. B. Pokorny, D. Garrido, B. W. Schuller, D. Zhang, and P. B. Marschik, “Vocalisation Repertoire at the End of the First Year of Life: An Exploratory Comparison of Rett Syndrome and Typical Development,” Journal of Developmental and Physical Disabilities, 3 2022. 17 pages, to appear (IF: 1.710 (2020))

  • S. Amiriparian, T. Hübner, V. Karas, M. Gerczuk, S. Ottl, and B. W. Schuller, “DeepSpectrumLite: A PowerEfficient Transfer Learning Framework for Embedded Speech and Audio Processing from Decentralised Data,” Frontiers in Artificial Intelligence, section Language and Computation, 2022. 16 pages, to appear

 

2021

 

  • 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, “An Evaluation of Speech-Based Recognition of Emotional and Physiological Markers of Stress”, Frontiers in Computer Science, section HumanMedia Interaction, 2021. 28 pages, to appear

  • M. Gerczuk, S. Amiriparian, S. Ottl, and B. Schuller, “EmoNet: A Transfer Learning Framework for MultiCorpus Speech Emotion Recognition”, IEEE Transactions on Affective Computing, vol. 13, 2022. 18 pages, to appear (IF: 10.506 (2020))
  • S. Liu, J. Han, E. Laporta Puyal, S. Kontaxis, S. Sun, P. Locatelli, J. Dineley, F. B. Pokorny, G. D. Costa, L. Leocani, A. I. Guerrero, C. Nos, A. Zabalza, P. S. Sørensen, M. Buron, M. Magyari, Y. Ranjan, Z. Rashid, P. Conde, C. Stewart, A. A. Folarin, R. Dobson, R. Bailón, S. Vairavan, N. Cummins, V. A. Narayan, M. Hotopf, G. Comi, B. W. Schuller, and RADAR-CNS Consortium, “Fitbeat: COVID-19 Estimation based on Wristband Heart Rate”, Pattern Recognition, Special Issue on AI for Combating COVID-2019, 2021. 34 pages, to appear (IF: 7.740 (2021)) open access
  • L. Stappen, A. Baird, L. Schumann, and B. Schuller, “The Multimodal Sentiment Analysis in Car Reviews (MuSeCaR) Dataset: Collection, Insights and Improvements”, IEEE Transactions on Affective Computing, vol. 12, 2021. 16 pages, to appear (IF: 10.506 (2020))  
  • B. Schuller, A. Baird, A. Gebhard, S. Amiriparian, G. Keren, M. Schmitt, and N. Cummins. New Avenues in Audio Intelligence: Towards Holistic Real-life Audio Understanding. Trends in Hearing, 2021. 18 pages, to appear (IF: 3.293 (2020))
  • M. Song, A. Mallol-Ragolta, E. Parada-Cabaleiro, Z. Yang, S. Liu, Z. Ren, Z. Zhao, & B. W. Schuller (2021). Frustration Recognition from Speech During Game Interaction Using Wide Residual Networks. Virtual Reality & Intelligent Hardware, 3(1), 76–86.   Open Access
  • L. Stappen, A. Baird, E. Cambria, & B. W. Schuller (2021). Sentiment Analysis and Topic Recognition in Video Transcriptions. IEEE Intelligent Systems Magazine, 36(2), 88–95.
  • K. D. Bartl-Pokorny, F. B. Pokorny, A. Batliner, S. Amiriparian, A. Semertzidou, F. Eyben, E. Kramer, F. Schmidt, R. Schönweiler, M. Wehler, & B. W. Schuller (2021). The voice of COVID-19: Acoustic correlates of infection in sustained vowels. Journal of the Acoustical Society of America, 146.   Open Access
  • S. Liu, G. Keren, E. Parada-Cabaleiro, & B. W. Schuller (2021). N-HANS: A neural network-based toolkit for in-the-wild audio enhancement. Multimedia Tools and Applications, 1–25. Open Access

2020

  • A. Batliner, S. Hantke, and B. Schuller, “Ethics and Good Practice in Computational Paralinguistics,“ IEEE Transactions on Affective Computing, 2020, 19 pages, to appear [ pdf ]
  • E. Parada-Cabaleiro, A. Batliner, A. Baird, and B. W. Schuller, “The Perception of Emotional Cues by Children in Artificial Background Noise,” International Journal of Speech Technology, vol. 23, pp. 169-182, 2020.
  • P. Wu, X. Sun, Z. Zhao, H. Wang, S. Pan, and B. Schuller, “Classification of Lung Nodules Based on Deep Residual Networks and Migration Learning,” Computational Intelligence and Neuroscience, vol. 2020, 8975078, 10 pages, 2020. [ open access]

2019

  • F. Dong, K. Qian, Z. Ren, A. Baird, X. Li, Z. Dai, B. Dong, F. Metze, Y. Yamamoto, and B. Schuller, “Machine Listening for Heart Status Monitoring: Introducing and Benchmarking HSS – the Heart Sounds Shenzhen Corpus,” IEEE Journal of Biomedical and Health Informatics, vol. 23, 2019. 11 pages, to appear
  • J. Han, Z. Zhang, Z. Ren, and B. Schuller, “Exploring Perception Uncertainty for Emotion Recognition in Dyadic Conversation and Music Listening,” Cognitive Computation, Special Issue on Affect Recognition in Multimodal Language, vol. 11, 2019. 10 pages, to appear
  • S. Amiriparian, N. Cummins, M. Gerczuk, S. Pugachevskiy, S. Ottl, and B. Schuller, “Are You Playing a Shooter Again?!“ Deep Representation Learning for Audio-based Video Game Genre Recognition,” IEEE Transactions on Games, vol. 11, 10.1109/TG.2019.2894532, 11 pages, January 2019.
  • J. Han, Z. Zhang, Z. Ren, and B. Schuller, “EmoBed: Strengthening Monomodal Emotion Recognition via Training with Crossmodal Emotion Embeddings,” IEEE Transactions on Affective Computing, vol. 10, 2019. 12 pages, to appear
  • Z. Zhang, J. Han, K. Qian, C. Janott, Y. Guo, and B. Schuller, “Snore-GANs: Improving Automatic Snore Sound Classification with Synthesized Data,” IEEE Journal of Biomedical and Health Informatics, vol. 23, 2019. 11 pages, to appear
  • J. Kossaifi, R. Walecki, Y. Panagakis, J. Shen, M. Schmitt, F. Ringeval, J. Han, V. Pandit, B. Schuller, K. Star, E. Hajiyev, and M. Pantic, “SEWA DB: A Rich Database for Audio-Visual Emotion and Sentiment Research in the Wild,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 41, 2019. 17 pages, to appear
  • S. Amiriparian, J. Han, M. Schmitt, A. Baird, A. Mallol-Ragolta, M. Milling, M. Gerczuk, and B. Schuller, “Synchronisation in Interpersonal Speech,” Frontiers in Robotics and AI, section Humanoid Robotics, Special Issue on Computational Approaches for Human-Human and Human-Robot Social Interactions,
    vol. 6, 4578452019, 10 pages, 2019. [ open access]
  • C. Janott, M. Schmitt, C. Heiser, W. Hohenhorst, M. Herzog, M. C. Llatas, W. Hemmert, and B. Schuller, “VOTE versus ACLTE: Vergleich zweier Schnarchger¨auschklassifikationen mit Methoden des maschinellen Lernens,” HNO, vol. 67, no. 9, pp. 670-678, 2019.
  • G. Keren, S. Sabato, and B. Schuller, “Analysis of Loss Functions for Fast Single-Class Classification,” Knowledge and Information Systems, vol. 59, doi: 10.1007/s10115-019-01395-6, 22 pages, 2019. [invited as one of best papers from ICDM 2018]
  • B. Schuller, “Responding to Uncertainty in Emotion Recognition,” Journal of Information, Communication & Ethics in Society, vol. 17, no. 3, pp. 299-303, August 2019.
  • S. Hantke, T. Olenyi, C. Hausner, and B. Schuller, “Large-scale Data Collection and Analysis via a Gamified Intelligent Crowdsourcing Platform,” International Journal of Automation and Computing, vol. 16, pp. 427-436, August 2019.
  • Z. Zhao, Z. Bao, Y. Zhao, Z. Zhang, N. Cummins, Z. Ren, and B. Schuller, “Exploring Deep Spectrum Representations via Attention-based Recurrent and Convolutional Neural Networks for Speech Emotion Recognition,” IEEE Access, pp. 9715-97525, July 2019. [open access]
  • Z. Zhang, J. Han, E. Coutinho, and B. Schuller, “Dynamic Difficulty Awareness Training for Continuous Emotion Prediction,” IEEE Transactions on Multimedia, vol. 20, pp. 1289-1301, May 2019.
  • J. Han, Z. Zhang, N. Cummins, and B. Schuller, “Adversarial Training in Affective Computing and Sentiment Analysis: Recent Advances and Perspectives,” IEEE Computational Intelligence Magazine, special issue on Computational Intelligence for Affective Computing and Sentiment Analysis, pp. 68-81, April 2019.  [preprint]
  • K. Qian, M. Schmitt, C. Janott, Z. Zhang, C. Heiser, W. Hohenhorst, M. Herzog, W. Hemmert, and B. Schuller, “A Bag of Wavelet Features for Snore Sound Classification,” Annals of Biomedical Engineering, vol. 47, pp. 1000-1011, April 2019.
  • E. Parada-Cabaleiro, G. Costantini, A. Batliner, M. Schmitt, and B. W. Schuller, “DEMoS – An Italian Emotional Speech Corpus – Elicitation methods, machine learning, and perception,” Language Resources and Evaluation, vol. 53, pp. 1-43, February 2019.
  • B. Schuller, “Micro-Expressions – A Chance for Computers to Beat Humans at Revealing Hidden Emotions?,” IEEE Computer Magazine, vol. 52, pp. 4-5, February 2019.
  • B. Schuller, F. Weninger, Y. Zhang, F. Ringeval, A. Batliner, S. Steidl, F. Eyben, E. Marchi, A. Vinciarelli, K. Scherer, M. Chetouani, and M. Mortillaro, “Affective and Behavioural Computing: Lessons Learnt from the First Computational Paralinguistics Challenge,” Computer Speech and Language, vol. 53, pp. 156-180, January 2019.

2018

  • K. Veselkov and B. Schuller, “The age of data analytics: converting biomedical data into actionable insights,” Methods, Special Issue on Health Informatics and Translational Data Analytics, vol. 151, pp. 1-2, December 2018.
  • N. Cummins, B. W. Schuller, and A. Baird, “Speech analysis for health: Current state-of-the-art and the increasing impact of deep learning,” Methods, Special Issue on Health Informatics and Translational Data Analytics, vol. 151, pp. 41-54, December 2018.
  • K. Grabowski, A. Rynkiewicz, A. Lassalle, S. Baron-Cohen, B. Schuller, N. Cummins, A. E. Baird, J. Podgórska-Bednarz, A. Pieniazek, and I. Lucka, “Emotional expression in psychiatric conditions – new technology for clinicians,” Psychiatry and Clinical Neurosciences, vol. 73, pp. 50-62, November 2018.
  • S. Jing, X. Mao, L. Chen, M. C. Comes, A. Mencattini, G. Raguso, F. Ringeval, B. Schuller, C. D. Natale, and E. Martinelli, “A closed-form solution to the graph total variation problem for continuous emotion profiling in noisy environment,” Speech Communication, vol. 104, pp. 66–72, November 2018.
  • K. Qian, C. Janott, Z. Zhang, J. Deng, A. Baird, C. Heiser, W. Hohenhorst, M. Herzog, W. Hemmer, and B. Schuller, “Teaching Machines on Snoring: A Benchmark on Computer Audition for Snore Sound Excitation Localisation,” Archives of Acoustics, vol. 43, pp. 465-475, November 2018.  [open access]
  • F. B. Pokorny, K. D. Bartl-Pokornya, C. Einspieler, D. Zhang, R. Vollmann, S. Bölte, H. Tager-Flusberg, M. Gugatschka, B.W. Schuller, and P. B. Marschik, “Typical vs. atypical: Combining auditory Gestalt perception and acoustic analysis of early vocalisations in Rett syndrome,” Research in Developmental Disabilities, vol. 82, pp. 109-119, November 2018.
  • J. Han, Z. Zhang, G. Keren, and B. Schuller, “Emotion Recognition in Speech with Latent Discriminative Representations Learning,” Acta Acustica united with Acustica, vol. 104, pp. 737-740, September/October 2018. [open access]
  • D. Schuller and B. Schuller, “The Age of Artificial Emotional Intelligence,” IEEE Computer Magazine, Special Issue on The Future of Artificial Intelligence, vol. 51, September 2018, pp. 38-46.
  • A. Mencattini, F. Mosciano, M. Colomba Comes, T. De Gregorio, G. Raguso, E. Daprati, F. Ringeval, B. Schuller, and E. Martinelli, “An emotional modulation model as signature for the identification of children developmental disorders,” Scientific Reports, 14487, 12 pages, September 2018.  [open access]
  • G. Keren, N. Cummins, and B. Schuller, “Calibrated Prediction Intervals for Neural Network Regressors,” IEEE Access, vol. 6, pp. 54033-54041, September 2018. [open access]
  • E. Marchi, B. Schuller, A. Baird, S. Baron-Cohen, A. Lassalle, H. O’Reilly, D. Pigat, P. Robinson, I. Davies, T. Baltrusaitis, O. Golan, S. Fridenson-Hayo, S. Tal, S. Newman, N. MeirGoren, A. Camurri, S. Piana, S. Bölte, M. Sezgin, N. Alyuz, A. Rynkiewicz, and A. Baranger, “The ASC-Inclusion Perceptual Serious Gaming Platform for Autistic Children,” IEEE Transactions on Computational Intelligence and AI in Games, pp. 1-12, August 2018.
  • S. Hantke, A. Abstreiter, N. Cummins, and B. Schuller, “Trustability-based Dynamic Active Learning for Crowdsourced Labelling of Emotional Audio Data,” IEEE Access, vol. 6, 2018. pp. 42142-42155, July 2018.  [open access]
  • O. Rudovic, J. Lee, M. Dai, B. Schuller, and R. W. Picard, “Personalized machine learning for robot perception of affect and engagement in autism therapy,” Science Robotics, vol. 3, doi: 10.1126/scirobotics.aao6760, 11 pages, June 2018.   [open access]
  • B. Schuller, “What Affective Computing Reveals on Autistic Children’s Face of Joy or Fear,” IEEE Computer Magazine, vol. 51,  pp. 7-8, June 2018.  [open access]
  • B. Schuller, “Speech Emotion Recognition: Two Decades in a Nutshell, Benchmarks, and Ongoing Trends,” Communications of the ACM, vol. 61, pp. 90-99, May 2018. 
  • A. Baird, S. H. Jorgensen, E. Parada-Cabaleiro, S. Hantke, N. Cummins, and B. Schuller, “The Perception of Vocal Traits in Synthesized Voices: Age, Gender, and Human Likeness,” Journal of the Audio Engineering Society, Special Issue on Augmented and Participatory Sound and Music Interaction using Semantic Audio, vol. 66, pp. 277-285, April 2018.
  • Z. Zhang, J. Han, J. Deng, X. Xu, F. Ringeval, and B. Schuller, “Leveraging Unlabelled Data for Emotion Recognition with Enhanced Collaborative Semi-Supervised Learning,” IEEE Access, vol. 6, pp. 22196 - 22209, April 2018.  [open access]
  • Z. Ren, K. Qian, Z. Zhang, V. Pandit, A. Baird, and B. Schuller, “Deep Scalogram Representations for Acoustic Scene Classification,” IEEE/CAA Journal of Automatica Sinica, 2018. vol. 5, pp. 662-669, April 2018.   [open access]
  • C. Janott, M. Schmitt, Y. Zhang, K. Qian, V. Pandit, Z. Zhang, C. Heiser, W. Hohenhorst, M. Herzog, W. Hemmert, and B. Schuller, “Snoring Classified: The Munich Passau Snore Sound Corpus,” Computers in Biology and Medicine, vol. 94, pp. 106-118, March 2018. 
  • M. Freitag, S. Amiriparian, S. Pugachevskiy, N. Cummins, and B. Schuller, “auDeep: Unsupervised Learning of Representations from Audio with Deep Recurrent Neural Networks,” Journal of Machine Learning Research, vol. 18, pp. 1-5, February 2017 - December 2018.  [open access]
  • J. Deng, X. Xu, Z. Zhang, S. Fruhholz, and B. Schuller, “Semi-Supervised Autoencoders for Speech Emotion Recognition,” IEEE/ACM Transactions on Audio, Speech and Language Processing, vol. 26, pp. 31-43, January 2018.

 

2017

  • X. Xu, J. Deng, E. Coutinho, C. Wu, L. Zhao, and B. Schuller, “Connecting Subspace Learning and Extreme Learning Machine in Speech Emotion Recognition,” IEEE Transactions on Multimedia, vol. 20, 2017, 13 pages.
  • P. Tzirakis, G. Trigeorgis, M. A. Nicolaou, B. Schuller, and S. Zafeiriou, “End-to-End Multimodal Emotion Recognition using Deep Neural Networks,” IEEE Journal of Selected Topics in Signal Processing, Special Issue on End-to-End Speech and Language Processing, vol. 11, pp. 1301-1309, December 2017.
  • V. Pandit and B. Schuller, “A Novel Graphical Technique for Combinational Logic Representation and Optimization,” Complexity, vol. 2017, Article ID 9696342, 12 pages, 2017.  [open access]
  • D. Schuller and B. Schuller, “Automatic Speech Emotion Recognition in Dialogue and Human-Computer Interaction: A Survey,” International Journal of Automation and Computing, vol. 15, 2018. 10 pages, invited contribution, to appear
  • B. Schuller and D. Schuller, “Maschinelle Profilierung – Die KI kennt Sie,” digma – Zeitschrift für Datenrecht und Informationssicherheit, vol. 1, no. 4, 2017. 6 pages, to appear

Conference Proceedings

2022

  • B. W. Schuller, A. Batliner, S. Amiriparian, C. Bergler, M. Gerczuk, N. Holz, P. Larrouy-Maestri, S. P. Bayerl, K. Riedhammer, A. Mallol-Ragolta, M. Pateraki, H. Coppock, I. Kiskin, M. Sinka, and S. Roberts, “The ACM Multimedia 2022 Computational Paralinguistics Challenge: Vocalisations, Stuttering, Activity, & Mosquitos,” in Proceedings of the 30th ACM International Conference on Multimedia, MM 2022, (Lisbon, Portugal), ACM, ACM, 10 2022. 5 pages, to appear

  • X. He, A. Triantafyllopoulos, A. Kathan, M. Milling, T. Yan, S. T. Rajamani, L. Küster, M. Harrer, E. Heber, I. Grossmann, D. D. Ebert, and B. Schuller, “Depression Diagnosis and Forecast based on Mobile Phone Sensor Data,” in Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, EMBC 2022, (Glasgow, UK), IEEE, IEEE, 7 2022. 4 pages, to appear

  • X. Jing, S. Liu, E. Parada-Cabaleiro, A. Triantafyllopoulos, M. Song, Z. Yang, and B. Schuller, “A Temporaloriented Broadcast ResNet for COVID-19 Detection,” in Proceedings of the IEEE International Conference on Biomedical and Health Informatics (BHI), (Ioannina, Greece), IEEE, IEEE, 9 2022. 5 pages, to appear

  • V. Karas, M. K. Tellamekala, A. Mallol-Ragolta, M. Valstar, and B. Schuller, “Continuous-Time Audiovisual Fusion with Recurrence vs. Attention for In-The-Wild Affect Recognition,” in Proceedings The 3rd Workshop and Competition on Affective Behavior Analysis in-the-wild (ABAW), held in conjunction with the IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), (New Orleans, LA), IEEE/CVF, IEEE, 6 2022. 10 pages, to appear

  • A. Kathan, A. Triantafyllopoulos, X. He, M. Milling, T. Yan, S. T. Rajamani, L. Küster, M. Harrer, E. Heber, I. Grossmann, D. D. Ebert, and B. Schuller, “Journaling Data for Daily PHQ-2 Depression Prediction and Forecasting,” in Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, EMBC 2022, (Glasgow, UK), IEEE, IEEE, 7 2022. 4 pages, to appear

  • A. Mallol-Ragolta, S. Liu, and B. Schuller, “COVID19 Detection Exploiting Self-Supervised Learning Representations of Respiratory Sounds,” in Proceedings of the IEEE International Conference on Biomedical and Health Informatics (BHI), (Ioannina, Greece), IEEE, IEEE, 9 2022. 4 pages, to appear

  • A. Mallol-Ragolta, H. Cuesta, E. Gomez, and B. Schuller, “Multi-Type Outer Product-Based Fusion of Respiratory Sounds for Detecting COVID-19,” in Proceedings INTERSPEECH 2022, 23rd Annual Conference of the International Speech Communication Association, (Incheon, South Korea), ISCA, ISCA, 9 2022. 5 pages, to appear (acceptance rate: 50 %)

  • A. Mallol-Ragolta, F. Pokorny, K. Bartl-Pokorny, A. Semertzidou, and B. Schuller, “Triplet Loss-Based Models for COVID-19 Detection from Vocal Sounds,” in Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, EMBC 2022, (Glasgow, UK), IEEE, IEEE, 7 2022. 4 pages, to appear

  • A. Mallol-Ragolta, M. Maniadakis, G. Papadopoulos, and B. Schuller, “Time Series Representation using TS2Vec on Smartwatch Sensor Data for Fatigue Estimation,” in Proceedings 13th International Conference on Applied Human Factors and Ergonomics, AHFE, (New York City, NY), 2022. 7 pages, to appear

  • V. Pandit and B. Schuller, “The Many-to-Many Mappings Between the Concordance Correlation Coefficient, the Mean Square Error and the Correlation Coefficient,” in Proceedings of the 20th International Conference on Numerical Analysis and Applied Mathematics, ICNAAM 2022, (Crete, Greece), European Society of Computational Methods in Sciences and Engineering (ESCMCE), 9 2022. 4 pages, to appear

  • S. T. Rajamani, K. Rajamani, A. Kathan, and B. Schuller, “Novel insights of induced sparsity on Multi-Time Attention Networks,” in Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, EMBC 2022, (Glasgow, UK), IEEE, IEEE, 7 2022. 4 pages, to appear

  • S. T. Rajamani, K. Rajamani, P. Rani, R. Barick, R. M. Sheshadri, S. V. Aithal, R. E. Ramalingam, S. D. Gowda, and B. Schuller, “Novel no-reference multi-dimensional perceptual similarity metric,” in Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, EMBC 2022, (Glasgow, UK), IEEE, IEEE, 7 2022. 4 pages, to appear

  • M. Song, E. Parada-Cabaleiro, Z. Yang, K. Qian, B. W. Schuller, and Y. Yamamoto, “Parallelising 2D-CNNs and Transformers: A Cognitive-based approach for Automatic Recognition of Learners’ English Proficiency,” in Proceedings 5th International Conference on Intelligent Human Systems Integration, IHSI 2022, (Venice, Italy), Springer, 2 2022. 8 pages, to appear

  • A. Triantafyllopoulos, M. Fendler, A. Batliner, M. Gerczuk, S. Amiriparian, T. Berghaus, and B. W. Schuller, “Distinguishing between pre- and post-treatment in the speech of patients with chronic obstructive pulmonary disease,” in Proceedings INTERSPEECH 2022, 23rd Annual Conference of the International Speech Communication Association, (Incheon, South Korea), ISCA, ISCA, 9 2022. 5 pages, to appear (acceptance rate: 50 %)

  •  A. Triantafyllopoulos, S. Ottl, A. Gebhard, E. RituertoGonzalez, M. Jaumann, S. Hüttner, V. Dieter, P. Schneeweiss, I. Krauss, M. Gerczuk, S. Amiriparian, and B. Schuller, “Fatigue Prediction in Outdoor Running Conditions using Audio Data,” in Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, EMBC 2022, (Glasgow, UK), IEEE, IEEE, 7 2022. 4 pages, to appear

  • A. Triantafyllopoulos, S. Zänkert, A. Baird, J. Konzok, B. Kudielka, and B. Schuller, “Insights on Modelling Physiological, Appraisal, and Affective Indicators of Stress using Audio Features,” in Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, EMBC 2022, (Glasgow, UK), IEEE, IEEE, 7 2022. 4 pages, to appear

  • A. Triantafyllopoulos, J. Wagner, H. Wierstorf, M. Schmitt, U. Reichel, F. Eyben, F. Burkhardt, and B. W. Schuller, “Probing speech emotion recognition transformers for linguistic knowledge,” in Proceedings INTERSPEECH 2022, 23rd Annual Conference of the International Speech Communication Association, (Incheon, South Korea), ISCA, ISCA, 9 2022. 5 pages, to
    appear (acceptance rate: 50 %)

  • Z. Yang, X. Jing, A. Triantafyllopoulos, M. Song, I. Aslan, and B. W. Schuller, “An Overview & Analysis of Sequenceto-Sequence Emotional Voice Conversion,” in Proceedings INTERSPEECH 2022, 23rd Annual Conference of the International Speech Communication Association, (Incheon, South Korea), ISCA, ISCA, 9 2022. 5 pages, to appear (acceptance rate: 50 %)

  • T. Yan, H. Meng, S. Liu, E. Parada-Cabaleiro, Z. Ren, and B. W. Schuller, “Convolutional Transformer with Adaptive Position Embedding for COVID-19 Detection from Cough Sounds,” in Proceedings 47th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022, (Singapore), IEEE, IEEE, 5 2022. 5 pages, to appear (acceptance rate: 45 %)

2021

  • M. Song, E. Parada-Cabaleiro, Z. Yang, K. Qian, B. W. Schuller, and Y. Yamamoto, “Parallelising CNNs and Transformers: A Cognitive-based approach for Automatic Recognition of Learners’ English Proficiency,” in Proceedings 5th International Conference on Intelligent Human Systems Integration, IHSI 2022, (Venice, Italy), Springer, February 2022. 6 pages, to appear

  • S. Amiriparian and B. Schuller, “AI Hears Your Health: Computer Audition for Health Monitoring,” in Proceedings of ICT for Health, Accessibility and Wellbeing, ICIHAW, Lecture Notes in Communications in Computer and Information Science, (Larnaca, Cyprus), Springer, November 2021. 6 pages, invited contribution, to appear

  • A. Baird, L. Stappen, L. Christ, L. Schumann, E.-M. Messner, and B. W. Schuller, “A Physiologically-Adapted Gold Standard for Arousal during Stress,” in Proceedings of the 2nd Multimodal Sentiment Analysis Challenge and Workshop (MuSe) co-located with the 29th ACM International Conference on Multimedia, MM 2021, (Chengdu, China), ACM, ACM, October 2021. 5 pages, to appear open access

  • V. Karas and B. Schuller, “Recognising Covid-19 from Coughing using Ensembles of SVMs and LSTMs with Handcrafted and Deep Audio Features,” in Proceedings INTERSPEECH 2021, 22nd Annual Conference of the International Speech Communication Association, (Brno, Czechia), ISCA, ISCA, September 2021. 5 pages, to appear open access

  • S. Liu, A. Mallol-Ragolta, and B. Schuller, “COVID-19 Detection with a Novel Multi-Type Deep Fusion Method using Breathing and Coughing Information,” in Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, EMBC 2021, (virtual), IEEE, IEEE, October 2021. 4 pages, to appear

  • A. Mallol-Ragolta, A. Semertzidou, M. Pateraki, and B. Schuller, “harAGE: A Novel Multimodal Smartwatch-based Dataset for Human Activity Recognition,” in Proceedings 16th IEEE International Conference on Automatic Face & Gesture Recognition, FG 2021, (Jodhpur, India), IEEE, IEEE, December 2021. 7 pages, to appear

  • A. Mallol-Ragolta, S. Liu, and B. W. Schuller, “The Filtering Effect of Face Masks in their Detection from Speech,” in Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, EMBC 2021, (virtual), IEEE, IEEE, October 2021. 4 pages, to appear

  • S. T. Rajamani, K. Rajamani, and B. W. Schuller, “Towards an Efficient Deep Learning Model for Emotion and Theme Recognition in Music,” in Proceedings IEEE 23rd International Workshop on Multimedia Signal Processing, MMSP 2021, (Tampere, Finland), pp. 1–6, IEEE, IEEE, October 2021. 6 pages, to appear

  • L. Stappen, L. Schumann, A. Batliner, and B. Schuller, “Embracing and Exploiting Annotator Emotional Subjectivity: An Affective Rater Ensemble Model,” in Proceedings What’s Next in Affect Modelling Workshop at the 9th biannual Conference on Affective Computing and Intelligent Interaction (ACII 2021), (Nara, Japan), AAAC, IEEE, September 2021. 7 pages, to appear

  • L. Stappen, B. Schuller, E. M. Messner, E. Cambria, and G. Zhao, “MuSe 2021 Challenge: Multimodal Emotion, Sentiment, Physiological-Emotion, and Stress Detection,” in Proceedings of the 29th ACM International Conference on Multimedia, MM 2021, (Chengdu, China), pp. 5706–5707, ACM, ACM, October 2021 open access

  • L. Stappen, L. Schumann, B. Sertolli, A. Baird, B. Weigel, E. Cambria, and B. W. Schuller, “MuSe-Toolbox: The Multimodal Sentiment Analysis Continuous Annotation Fusion and Discrete Class Transformation Toolbox,” in Proceedings of the 2nd Multimodal Sentiment Analysis Challenge and Workshop (MuSe) co-located with the 29th ACM International Conference on Multimedia, MM 2021,
    (Chengdu, China), ACM, ACM, October 2021. 8 pages, to appear open access
  • L. Stappen, A. Baird, L. Christ, L. Schumann, B. Sertolli, E.-M. Messner, E. Cambria, G. Zhao, and B. W. Schuller, “The MuSe 2021 Multimodal Sentiment Analysis Challenge: Sentiment, Emotion, Physiological-Emotion, and Stress,” in Proceedings of the 2nd Multimodal Sentiment Analysis Challenge and Workshop (MuSe) co-located with the 29th ACM International Conference on Multimedia,
    MM 2021, (Chengdu, China), ACM, ACM, October 2021. 9 pages, to appear open access
  • A. Triantafyllopoulos, M. Milling, K. Drossos, and B. W. Schuller, “Fairness and Underspecification in Acoustic Scene Classification: The Case for Disaggregated Evaluations,” in Proceedings of The 6th Workshop on Detection and Classification of Acoustic Scenes and Events, DCASE 2021, (online), IEEE, November 2021. 5 pages, to appear open access
  • M. Song, K. Qian, B. Chen, K. Okabayashi, E. Parada-Cabaleiro, Z. Yang, S. Liu, K. Togami, I. Hidaka, Y. Wang, B. W. Schuller, & Y. Yamamoto (2021). Predicting Group Work Performance from Physical Handwriting Features in a Smart English Classroom. In Proceedings of the 5th International Conference on Digital Signal Processing, ICDSP 2021. ACM. 5 pages, to appear
  • S. Tirunellai Rajamani, K. Tirunellai Rajamani, A. Mallol-Ragolta, S. Liu, & B. Schuller (2021). A Novel Attention-based Gated Recurrent Unit and its Efficacy in Speech Emotion Recognition. In Proceedings 46th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2021 (pp. 6294–6298). IEEE.

  • A. Triantafyllopoulos, & B. Schuller (2021). The Role of Task and Acoustic Similarity in Audio Transfer Learning: Insights from the Speech Emotion Case. In Proceedings 46th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2021 (pp. 7268–7272). IEEE.

  • A. Baird, S. Amiriparian, M. Milling, & B. Schuller (2021). Emotion Recognition in Public Speaking Scenarios Utlising an LSTM-RNN Approach with Attention. In Proceedings IEEE Spoken Language Technology Workshop, SLT. IEEE.

  • B. W. Schuller, A. Batliner, C. Bergler, C. Mascolo, J. Han, I. Lefter, H. Kaya, S. Amiriparian, A. Baird, L. Stappen, S. Ottl, M. Gerczuk, P. Tzirakis, C. Brown, J. Chauhan, A. Grammenos, A. Hasthanasombat, D. Spathis, T. Xia, P. Cicuta, Leon J., M. Rothkranz, J. Zwerts, J. Treep, & C. Kaandorp (2021). The INTERSPEECH 2021 Computational Paralinguistics Challenge: COVID-19 Cough, COVID-19 Speech, Escalation & Primates. In Proceedings INTERSPEECH 2021, 22nd Annual Conference of the International Speech Communication Association. ISCA. 5 pages, to appear

  • T. Yan, H. Meng, E. Cabaleiro, S. Liu, M. Song, & B. Schuller (2021). Coughing-based Recognition of Covid-19 with Spatial Attentive ConvLSTM Recurrent Neural Networks. In Proceedings INTERSPEECH 2021, 22nd Annual Conference of the International Speech Communication Association. ISCA. 5 pages, to appear

  • A. Mallol-Ragolta, H. Cuesta, E. Gomez, & B. Schuller (2021). Cough-based COVID-19 Detection with Contextual Attention Convolutional Neural Networks and Gender Information. In Proceedings INTERSPEECH 2021, 22nd Annual Conference of the International Speech Communication Association. ISCA. 5 pages, to appear

  • 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 INTERSPEECH 2021, 22nd Annual Conference of the International Speech Communication Association. ISCA. 5 pages, to appear

  • J. Dineley, G. Lavelle, D. Leightley, F. Matcham, S. Siddi, M. Teresa Penarrubia-Maria, K. White, A. Ivan, C. Oetzmann, S. Simblett, E. Dawe-Lane, S. Bruce, D. Stahl, J. M. Haro, T. Wykes, V. Narayan, M. Hotopf, B. Schuller, N. Cummins, & The RADAR-CNS Consortium (2021). Remote smartphone-based speech collection: acceptance and barriers in individuals with major depressive disorder. In Proceedings INTERSPEECH 2021, 22nd Annual Conference of the International Speech Communication Association. ISCA. 5 pages, to appear

  • A. Triantafyllopoulos, S. Liu, & B. Schuller (2021). Deep Speaker Conditioning for Speech Emotion Recognition. In Proceedings 22nd IEEE International Conference on Multimedia and Expo, ICME 2021. IEEE.

  • M. Song, E. Parada-Cabaleiro, S. Liu, A. Baird, M. Milling, Z. Yang, & B. Schuller (2021). Supervised Contrastive Learning for in Game-Play Frustration Detection from Speech. In Proceedings International Conference on Human-Computer Interaction, HCI International 2021. SpringerNature. Open Access

2020

  • B. W. Schuller, A. Batliner, C. Bergler, E.-M. Messner, A. Hamilton, S. Amiriparian, A. Baird, G. Rizos, M. Schmitt, L. Stappen, H. Baumeister, A. D. MacIntyre, and S. Hantke, “The INTERSPEECH 2020 Computational Paralinguistics Challenge: Elderly Emotion, Breathing & Masks,” in Proceedings of INTERSPEECH 2020, 21st Annual Conference of the International Speech Communication Association, (Shanghai, China), ISCA, ISCA, September 2020. 5 pages, to appear
  • A. Baird, M. Song, and B. Schuller, “Interaction with the Soundscape – Exploring An Emotional Audio Generation Approach for Improved Individual Wellbeing,” in Proceedings of the 22nd International Conference on Human-Computer Interaction, HCI International 2020 (C. Stephanidis, ed.), (Copenhagen, Denmark), Springer, July 2020. 14 pages, to appear
  • G. Deshpande, S. Patel, S. Chanda, P. Patil, V. Agrawal, and B. Schuller, “Laughter as a Controller in a Stress Buster Game,” in Proceedings of the 14th EAI International Conference on Pervasive Computing Technologies for Healthcare, EAI Pervasive Health, (Atlanta, GA), European Alliance for Innovation, EAI, May 2020. 8 pages, to appear
  • S. Liu, J. Jiao, Z. Zhao, J. Dineley, N. Cummins, and B. Schuller, “Hierarchical Component Attention Based Speaker Turn Embedding for Emotion Recognition,” in Proceedings of the 33rd International Joint Conference on Neural Networks (IJCNN), (Glasgow, UK), pp. 1–8, INNS/IEEE, IEEE, July 2020. to appear
  • A. Mallol-Ragolta, S. Liu, N. Cummins, and B. Schuller, “A Curriculum Learning Approach for Pain Intensity Recognition from Facial Expressions,” in Proceedings 15th IEEE International Conference on Automatic Face & Gesture Recognition, FG 2020, (Buenos Aires, Argentina), IEEE, IEEE, May 2020.
    5 pages, to appear
  • Z. Ren, A. Baird, J. Han, Z. Zhang, and B. Schuller, “Generating and Protecting against Adversarial Attacks for Deep Speechbased Emotion Recognition Models,” in Proceedings of the 45th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020, (Barcelona, Spain), IEEE, IEEE, May 2020. 5 pages, to appear
  • G. Rizos, A. Baird, M. Elliott, and B. Schuller, “StarGAN for Emotional Speech Conversion: Validated by Data Augmentation of End-to-End Emotion Recognition,” in Proceedings of the 45th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020, (Barcelona, Spain), IEEE, IEEE,
    May 2020. 5 pages, to appear
  • Z. Zhao, Z. Bao, Z. Zhang, N. Cummins, H. Wang, and B. Schuller, “Hierarchical Attention Transfer Networks for Depression Assessment from Speech,” in Proceedings 45th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020, (Barcelona, Spain), IEEE, IEEE, May 2020. 5 pages, to appear
  • E. Parada-Cabaleiro, A. Batliner, and B. Schuller, “A Diplomatic Edition of Il Lauro Secco: Ground Truth for OMR of White Mensural Notation,” in Proceedings of the 20th International Society for Music Information Retrieval Conference (ISMIR), Delft, The Netherlands, November 2019. 7 pages, to appear
  • A. Baird, S. Amiriparian, and B. Schuller, “Can Deep Generative Audio be Emotional? Towards an Approach for Personalised Emotional Audio Generation,” in Proceedings of the the IEEE 21st International Workshop on Multimedia Signal Processing (MMSP 2019), Kuala Lumpur, Malaysia, September 2019. 5 pages, to appear
  • A. Baird, S. Amiriparian, M. Berschneider, M. Schmitt, and B. Schuller, “Predicting Blood Volume Pulse and Skin Conductance from Speech: Introducing a Novel Database and Results,” in Proceedings of the IEEE 21st International Workshop on Multimedia Signal Processing (MMSP 2019), Kuala Lumpur, Malaysia, September 2019. 5 pages, to appear

2019

  • E. Parada-Cabaleiro, A. Batliner, and B. Schuller, “A Diplomatic Edition of Il Lauro Secco: Ground Truth for OMR of White Mensural Notation,” in Proceedings of the 20th International Society for Music Information Retrieval Conference (ISMIR), Delft, The Netherlands, November 2019. 7 pages, to appear
  • A. Baird, S. Amiriparian, and B. Schuller, “Can Deep Generative Audio be Emotional? Towards an Approach for Personalised Emotional Audio Generation,” in Proceedings of the the IEEE 21st International Workshop on Multimedia Signal Processing (MMSP 2019), Kuala Lumpur, Malaysia, September 2019. 5 pages, to appear
  • A. Baird, S. Amiriparian, M. Berschneider, M. Schmitt, and B. Schuller, “Predicting Blood Volume Pulse and Skin Conductance from Speech: Introducing a Novel Database and Results,” in Proceedings of the IEEE 21st International Workshop on Multimedia Signal Processing (MMSP 2019), Kuala Lumpur, Malaysia, September 2019. 5 pages, to appear
  • L. Stappen, V. Karas, N. Cummins, F. Ringeval, K. Scherer, and B. Schuller, “From Speech to Facial Activity: Towards Cross-modal Sequence-to-Sequence Attention Networks,” in Proceedings of the IEEE 21st International Workshop on Multimedia Signal Processing (MMSP 2019), Kuala Lumpur, Malaysia, September 2019. 6 pages, to appear
  • F. Ringeval, B. Schuller, M. Valstar, N. Cummins, R. Cowie, M. Soleymani, M. Schmitt, S. Amiriparian, E.-M. Messner, L. Tavabi, S. Song, S. Alisamir, S. Lui, Z. Zhao, and M. Pantic, “AVEC 2019 Workshop and Challenge: State-of-Mind, Depression with AI, and Cross-Cultural Affect Recognition,” in Proceedings of the 9th International Workshop on Audio/Visual Emotion Challenge (AVEC), Nice, France, pp. 3-12, October 2019. 
  • B. W. Schuller, A. Batliner, C. Bergler, F. Pokorny, J. Krajewski, M. Cychosz, R. Vollmann, S.-D. Roelen, S. Schnieder, E. Bergelson, A. Cristià, A. Seidl, L. Yankowitz, E. Nöth, S. Amiriparian, S. Hantke, and M. Schmitt, “The INTERSPEECH 2019 Computational Paralinguistics Challenge: Styrian Dialects, Continuous Sleepiness, Baby Sounds & Orca Activity,” in Proceedings of INTERSPEECH, Graz, Austria, pp- 2378-2382, September 2019. [link]
  • A. Baird, E. Coutinho, J. Hirschberg, and B. W. Schuller, “Sincerity in Acted Speech: Presenting the Sincere Apology Corpus and Results,” in Proceedings of INTERSPEECH, Graz, Austria, pp. 539-543, September 2019. [link]
  • A. Baird, S. Amiriparian, N. Cummins, S. Strumbauer, J. Janson, E.-M. Messner, H. Baumeister, N. Rohleder, and B. W. Schuller, “Using Speech to Predict Sequentially Measured Cortisol Levels During a Trier Social Stress Test,” in Proceedings of INTERSPEECH, Graz, Austria, pp. 534-538, September 2019. [link]
  • Y. Guo, Z. Zhao, Y. Ma, and B. W. Schuller, “Speech Augmentation via Speaker-Specific Noise in Unseen Environment,” in Proceedings of INTERSPEECH, Graz, Austria, pp. 1781-1785, September 2019. [link]
  • A. Mallol-Ragolta, Z. Zhao, L. Stappen, N. Cummins, and B. W. Schuller, “A Hierarchical Attention Network-Based Approach for Depression Detection from Transcribed Clinical Interviews,” in Proceedings of INTERSPEECH, Graz, Austria, pp. 221-225, September 2019. [link]
  • M. Schmitt, N. Cummins, and B. W. Schuller, “Continuous Emotion Recognition in Speech – Do We Need Recurrence?,” in Proceedings of INTERSPEECH, Graz, Austria, pp. 2808-2812, September 2019. [link] 
  • X. Xu, J. Deng, N. Cummins, Z. Zhang, L. Zhao, and B. W. Schuller, “Autonomous emotion learning in speech: A view of zero-shot speech emotion recognition,” in Proceedings of INTERSPEECH 2019, Graz, Austria, pp. 949-953, September 2019. [link]
  • Z. Zhao, Z. Bao, Z. Zhang, N. Cummins, H. Wang, and B. W. Schuller, “Attention-enhanced Connectionist Temporal Classification for Discrete Speech Emotion Recognition,” in Proceedings of INTERSPEECH, Graz, Austria, pp. 206-210, September 2019. [link]
  • M. Schmitt and B. W. Schuller, “End-to-end Audio Classification with Small Datasets – Making It Work,” in Proceedings of the 27th European Signal Processing Conference (EUSIPCO), A Coruña, Spain, September 2019. 5 pages, to appear
  • M. Song, Z. Yang, A. Baird, E. Parada-Cabaleiro, Z. Zhang, Z. Zhao, and B. Schuller, “Audiovisual Analysis for Recognising Frustration during Game-Play: Introducing the Multimodal Game Frustration Database,” in Proceedings of the 8th Biannual Conference on Affective Computing and Intelligent Interaction (ACII 2019), Cambridge, UK, September 2019. to appear
  • S. Amiriparian, A. Awad, M. Gerczuk, L. Stappen, A. Baird, S. Ottl, and B. Schuller, “Audio-based Recognition of Bipolar Disorder Utilising Capsule Networks,” in Proceedings of the 32nd International Joint Conference on Neural Networks (IJCNN), Budapest, Hungary, paper N-19242, 7 pages, July 2019.
  • C. Li, Q. Zhang, Z. Zhao, L. Gu, N. Cummins, and B. Schuller, “Analysing and Inferring of Intimacy Based on fNIRS Signals and Peripheral Physiological Signals,” in Proceedings of the 32nd International Joint Conference on Neural Networks (IJCNN), Budapest, Hungary, July 2019. 8 pages, to appear
  • C. Janott, C. Rohrmeier, M. Schmitt, W. Hemmert, and B. Schuller, “Snoring – An Acoustic Definition,” in Proceedings of the 41st Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC 2019), Berlin, Germany, July 2019. 5 pages, to appear
  • J. Schiele, F. Rabe, M. Schmitt, M. Glaser, F. H¨aring, J. O. Brunner, B. Bauer, B. Schuller, C. Traidl-Hoffmann, and A. Damialis, “Automated Classification of Airborne Pollen using Neural Networks,” in Proceedings of the 41st Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), Berlin, Germany, July 2019. 5 pages, to appear
  • V. Pandit, M. Schmitt, N. Cummins, and B. Schuller, “I know how you feel now, and here’s why!: Demystifying Timecontinuous High Resolution Text-based Affect Predictions In the Wild,” in Proceedings of the 32nd IEEE International Symposium on Computer-Based Medical Systems (CBMS), Cordoba, Spain, June 2019, pp. 465-470. [link]
  • O. Rudovic, B. Schuller, C. Breazeal, and R. Picard, “Personalized Estimation of Engagement from Videos Using Active Learning with Deep Reinforcement Learning,” in Proceedings of the 9th IEEE International Workshop on Analysis and Modeling of Faces and Gestures (AMFG), Long Beach, CA, June 2019. 10 pages, to appear
  • J. Schmid, M. Schneider, A. Höß, and B. Schuller, “A Comparison of AI-Based Throughput Prediction for Cellular Vehicle-To-Server Communication,” in Proceedings of the 15th International Wireless Communications and Mobile Computing Conference (IWCMC), Tangier, Morocco, June 2019, pp. 471-476. [link]
  • A. Mallol-Ragolta, M. Schmitt, A. Baird, N. Cummins, and B. Schuller, “Performance Analysis of Unimodal and Multimodal Models in Valence-Based Empathy Recognition,” in Workshop Proceedings  of the 14th IEEE International Conference on Automatic Face & Gesture Recognition (FG), Lille, France, doi: 10.1109/FG.2019.8756517, 5 pages May 2019. [link]
  • J. Han, Z. Zhang, Z. Ren, and B. Schuller, “Implicit Fusion by Joint Audiovisual Training for Emotion Recognition in Mono Modality,” in Proceedings of the 44th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Brighton, UK, IEEE, IEEE, May 2019, pp. 5861-5865. [link] [slides]
  • Z. Ren, Q. Kong, J. Han, M. D. Plumbley, and B. W. Schuller, “Attention-based Atrous Convolutional Neural Networks: Visualisation and Understanding Perspectives of Acoustic Scenes,” in Proceedings of the 44th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Brighton, UK, IEEE, IEEE, May 2019, pp. 56-60. [link]  [slides]
  • L. Stappen, N. Cummins, E.-M. Rathner, H. Baumeister, J. Dineley, and B. Schuller, “Context Modelling Using Hierarchical Attention Networks for Sentiment and Self-Assessed Emotion Detection in Spoken Narratives,” in Proceedings of the 44th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Brighton, UK, IEEE, IEEE, May 2019, pp. 6680-6684. [link]

 

 

2018

  • G. Keren, S. Sabato, and B. Schuller, “Fast Single-Class Classification and the Principle of Logit Separation,” in Proceedings of the International Conference on Data Mining (ICDM), Singapore, Singapore, November 2018, pp. 227-236. [link]
  • Z. Ren, Q. Kong, K. Qian, and B. Schuller, “Attention-based Convolutional Neural Networks for Acoustic Scene Classification,” in Proceedings of the 3rd Detection and Classification of Acoustic Scenes and Events 2018 Workshop (DCASE), Surrey, UK, November 2018, pp. 39-43.  [link]  [slides]
  • F. Ringeval, B. Schuller, M. Valstar, R. Cowie, H. Kaya, M. Schmitt, S. Amiriparian, N. Cummins, D. Lalanne, A. Michaud, E. Ciftci, H. Gülec, A. A. Salah, and M. Pantic, “AVEC 2018 Workshop and Challenge: Bipolar Disorder and Cross-Cultural Affect Recognition,” in Proceedings of the 8th International Workshop on Audio/Visual Emotion Challenge (AVEC), co-located with the 26th ACM International Conference on Multimedia (MM), Seoul, South Korea, October 2018, pp. 3-13.
  • S. Hantke, M. Schmitt, P. Tzirakis, and B. Schuller, “EAT - The ICMI 2018 Eating Analysis and Tracking Challenge,” in Proceedings of the 20th ACM International Conference on Multimodal Interaction (ICMI), Boulder, CO, October 2018, pp. 559-563.
  • B. Sertolli, N. Cummins, A. Sengur, and B. Schuller, “Deep End-to-End Representation Learning for Food Type Recognition from Speech,” in Proceedings of the 20th ACM International Conference on Multimodal Interaction (ICMI), Boulder, CO, October 2018, pp. 574-578.
  • Y. Guo, J. Han, Z. Zhang, B. Schuller, and Y. Ma, “Exploring a New Method for Food Likability Rating Based on DT-CWT Theory,” in Proceedings of the 20th ACM International Conference on Multimodal Interaction (ICMI), Boulder, CO, October 2018, pp. 569-573.
  • Z. Ren, N. Cummins, J. Han, S. Schnieder, J. Krajewski, and B. Schuller, “Evaluation of the Pain Level from Speech: Introducing a Novel Pain Database and Benchmarks,” in Proceedings of the 13th ITG Conference on Speech Communication, Oldenburg, Germany, October 2018, pp. 56-60.
  • A. Sengur, F. Demir, H. Lu, S. Amiriparian, N. Cummins, and B. Schuller, “Compact Bilinear Deep Features for Environmental Sound Recognition,” in Proceedings of the International Conference on Artificial Intelligence and Data Mining (IDAP), Malatya, Turkey, September 2018. 5 pages.  PDF
  • A. Baird, E. Parada-Cabaleiro, C. Fraser, S. Hantke, and B. Schuller, “The Emotion of Synthetic Audio – A Dataset and Perception Results,” in Proceedings of the 12th Audio Mostly Conference on Interaction with Sound (Audio Mostly), Wrexham, UK, September 2018. 8 pages, to appear
  • V. Pandit, M. Schmitt, N. Cummins, F. Graf, L. Paletta, and B. Schuller, “How Good Is Your Model ‘Really’? On ‘Wildness’ of the In-the-wild Speech-based Affect Recognisers,” in Proceedings 20th International Conference on Speech and Computer (SPECOM), Leipzig, Germany, September 2018, pp. 490-500. 
  • J. Han, M. Schmitt, and B. Schuller, “You Sound Like Your Counterpart: Interpersonal Speech Analysis,” in Proceedings 20th International Conference on Speech and Computer (SPECOM), Leipzig, Germany, September 2018, pp. 188-197.
  • G. Keren, J. Han, and B. Schuller, “Scaling Speech Enhancement in Unseen Environments with Noise Embeddings,” in Proceedings The 5th International Workshop on Speech Processing in Everyday Environments held in conjunction with Interspeech 2018, Hyderabad, India, September 2018, pp. 25-29. [link]
  • B. Schuller, S. Steidl, A. Batliner, P. B. Marschik, H. Baumeister, F. Dong, S. Hantke, F. Pokorny, E.-M. Rathner, K. D. Bartl-Pokorny, C. Einspieler, D. Zhang, A. Baird, S. Amiriparian, K. Qian, Z. Ren, M. Schmitt, P. Tzirakis, and S. Zafeiriou, “The INTERSPEECH 2018 Computational Paralinguistics Challenge: Atypical & Self-Assessed Affect, Crying & Heart Beats,” in Proceedings of INTERSPEECH, Hyderabad, India, September 2018, pp. 122-126.  [link]
  • S. Hantke, C. Stemp, and B. Schuller, “Annotator Trustability-based Cooperative Learning Solutions for Intelligent Audio Analysis,” in Proceedings of INTERSPEECH, Hyderabad, India, September 2018, pp. 3504-3508.  [link]
  • A. Baird, E. Parada-Cabaleiro, S. Hantke, F. Burkhardt, N. Cummins, and B. Schuller, “The Perception and Analysis of the Likeability and Human Likeness of Synthesized Speech,” in Proceedings INTERSPEECH, Hyderabad, India, September 2018, pp. 2863-2867.  [link]
  • E. Parada-Cabaleiro, G. Costantini, A. Batliner, A. Baird, and B. Schuller, “Categorical vs Dimensional Perception of Italian Emotional Speech,” in Proceedings of INTERSPEECH, Hyderabad, India, September 2018, pp. 3638-3642.  [link]
  • E.-M. Rathner, J. Djamali, Y. Terhorst, B. Schuller, N. Cummins, G. Salamon, C. Hunger-Schoppe, and H. Baumeister, “How did you like 2017? Detection of language markers of depression and narcissism in personal narratives,” in Proceedings of INTERSPEECH, Hyderabad, India, September 2018, pp. 3388-3392.  [link]
  • E.-M. Rathner, Y. Terhorst, N. Cummins, B. Schuller, and H. Baumeister, “State of mind: Classification through self-reported affect and word use in speech,” in Proceedings INTERSPEECH, Hyderabad, India, September 2018, pp. 267-271.  [link]
  • S. Amiriparian, A. Baird, S. Julka, A. Alcorn, S. Ottl, S. Petrović, E. Ainger, N. Cummins, and B. Schuller, “Recognition of Echolalic Autistic Child Vocalisations Utilising Convolutional Recurrent Neural Networks,” in Proceedings of INTERSPEECH, Hyderabad, India, September 2018, pp. 2334-2338.  [link]
  • Z. Zhang, J. Han, K. Qian, and B. Schuller, “Evolving Learning for Analysing Mood-Related Infant Vocalisation,” in Proceedings INTERSPEECH, Hyderabad, India, September 2018, pp. 142-146.  [link]
  • Z. Zhang, A. Cristia, A. Warlaumont, and B. Schuller, "Automated Classification of Children's Linguistic versus Non-Linguistic Vocalisations," in Proceedings of INTERSPEECH, Hyderabad, India, September 2018, pp. 2588-2592.  [link]
  • J. Han, Z. Zhang, M. Schmitt, Z. Ren, F. Ringeval, and B. Schuller, “Bags in Bag: Generating Context-Aware Bags for Tracking Emotions from Speech,” in Proceedings of INTERSPEECH, Hyderabad, India, September 2018, pp. 3082-3086.  [link]
  • W. Han, H. Ruan, X. Chen, Z. Wang, H. Li, and B. Schuller, “Towards Temporal Modelling of Categorical Speech Emotion Recognition,” in Proceedings of INTERSPEECH, Hyderabad, India, September 2018, pp. 932–936.  [link]
  • E. Parada-Cabaleiro, A. Batliner, M. Schmitt, and B. Schuller, “Musical-Linguistic Annotations of Il Lauro Secco,” in Proceedings of the 19th International Society for Music Information Retrieval Conference (ISMIR), Paris, France, September 2018. pp. 461-467.  PDF
  • E. Parada-Cabaleiro, A. Batliner, M. Schmitt, S. Hantke, K. Scherer, and B. Schuller, “Identifying Emotions in Opera Singing: Implications of Adverse Acoustic Conditions,” in Proceedings of the 19th International Society for Music Information Retrieval Conference (ISMIR), Paris, France, September 2018. pp. 376-382.  PDF
  • S. Amiriparian, M. Freitag, N. Cummins, M. Gerzcuk, S. Pugachevskiy, and B. W. Schuller, “A Fusion of Deep Convolutional Generative Adversarial Networks and Sequence to Sequence Autoencoders for Acoustic Scene Classification,” in Proceedings of the 26th European Signal Processing Conference (EUSIPCO), Rome, Italy, September 2018. 5 pages, pp.977-981.  [link]
  • S. Amiriparian, M. Gerczuk, S. Ottl, N. Cummins, S. Pugachevskiy, and B. Schuller, “Bag-of-Deep-Features: Noise-Robust Deep Feature Representations for Audio Analysis,” in Proceedings of the 31st International Joint Conference on Neural Networks (IJCNN), Rio de Janeiro, Brazi, July 2018, pp. 2419-2425.  [link]  PPT
  • S. Amiriparian, M. Schmitt, N. Cummins, K. Qian, F. Dong, and B. Schuller, “Deep Unsupervised Representation Learning for Abnormal Heart Sound Classification,” in Proceedings of the 40th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), Honolulu, HI, July 2018, pp. 4776-4779.  [link]  PPT
  • F. Demir, A. Sengur, N. Cummins, S. Amiriparian, and B. Schuller, “Low-Level Texture Features for Snore Sound Discrimination,” in Proceedings of the 40th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), Honolulu, HI, July 2018, pp. 413-416.  [link]  [poster]
  • S. Hantke, C. Cohrs, M. Schmitt, B. Tannert, F. Lütkebohmert, M. Detmers, H. Schelhowe, and B. Schuller, “EmotAsS: An Emotion-driven Assistance System for Cognitively Impaired Individuals,” in Proceedings of the 16th International Conference on Computers Helping People with Special Needs (ICCHP), Linz, Austria, July 2018. pp. 486-494.  PDF
  • S. Song, S. Zhang, B. Schuller, L. Shen, and M. Valstar, “Noise Invariant Frame Selection: A Simple Method to Address the Background Noise Problem for Text-Independent Speaker Verification,” in Proceedings of the 31st International Joint Conference on Neural Networks (IJCNN), Rio de Janeiro, Brazil, July 2018, pp. 1-8.
  • J. Schmid, P. Heß, A. Höß, and B. Schuller, “Passive monitoring and geo-based prediction of mobile network vehicle-to server communication,” in Proceedings of the 14th International Wireless Communications and Mobile Computing Conference (IWCMC), Limassol, Cyprus, June 2018, pp. 483-1488.
  • A. Baird, S. Hantke, and B. Schuller, “Responsible Speech and Language Analysis: On Auditability, Benchmarking, Confidence, Data-Reliance & Explainability,” in Proceedings of the Legal and Ethical Issues Workshop, satellite of the 11th Language Resources and Evaluation Conference (LREC), Miyazaki, Japan, May 2018, 4 pages. [link]
  • S. Hantke, T. Appel, and B. Schuller, “The Inclusion of Gamification Solutions to Enhance User Enjoyment on Crowdsourcing Platforms,” in Proceedings of the first Asian Conference on Affective Computing and Intelligent Interaction (ACII Asia), Beijing, China, May 2018, 6 pages.  [link]
  • S. Hantke, T. Olenyi, C. Hausner, and B. Schuller, “VoiLA: An Online Intelligent Speech Analysis and Collection Platform,” in Proceedings of the first Asian Conference on Affective Computing and Intelligent Interaction (ACII Asia), Beijing, China, May 2018, 5 pages.  [link]
  • Y. Li, J. Tao, B. Schuller, S. Shan, D. Jiang, and J. Jia, “MEC 2017: Multimodal Emotion Recognition Challenge 2017,” in Proceedings of the first Asian Conference on Affective Computing and Intelligent Interaction (ACII Asia), Beijing, China, May 2018. 5 pages.  [link]
  • V. Pandit, N. Cummins, M. Schmitt, S. Hantke, F. Graf, L. Paletta, and B. Schuller, “Tracking Authentic and In-the-wild Emotions using Speech,” in Proceedings of the first Asian Conference on Affective Computing and Intelligent Interaction (ACII Asia), Beijing, China, May 2018. 6 pages.  [link]
  • H.-J. Vögel, C. Süß, V. Ghaderi, R. Chadowitz, E. André, N. Cummins, B. Schuller, J. Härri, R. Troncy, B. Huet, M. Önen, A. Ksentini, J. Conradt, A. Adi, A. Zadorojniy, J. Terken, J. Beskow, A. Morrison, K. Eng, F. Eyben, S. A. Moubayed, and S. Müller, “Emotion-awareness for intelligent Vehicle Assistants: a research agenda,” in Proceedings of the First Workshop on Software Engineering for AI in Autonomous Systems, SEFAIAS, co-located with the 40th International Conference on Software Engineering, ICSE, Gothenburg, Sweden, May 2018, pp. 11-15.
  • G. Hagerer, N. Cummins, F. Eyben, and B. Schuller, “Robust Laughter Detection for Mobile Wellbeing Sensing on Wearable Devices,” in Proceedings of the 8th International Conference on Digital Health (DH), Lyon, France, April 2018, pp. 156-157.  [link]
  • Z. Ren, N. Cummins, V. Pandit, J. Han, K. Qian, and B. Schuller, “Learning Image-based Representations for Heart Sound Classification,” in Proceedings of the 8th International Conference on Digital Health (DH), Lyon, France, April 2018, pp. 143-147.  [link]  PPT
  • N. Cummins, S. Amiriparian, S. Ottl, M. Gerczuk, M. Schmitt, and B. Schuller, “Multimodal Bag-of-Words for Cross Domains Sentiment Analysis,” in Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Calgary, Canada, April 2018, pp. 4954-4958.  [link]
  • P. Tzirakis, J. Zhang, and B. Schuller, “End-to-End Speech Emotion Recognition using Deep Neural Networks,” in Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Calgary, Canada, April 2018, pp. 5089-5093.  [link]
  • J. Han, Z. Zhang, Z. Ren, F. Ringeval, and B. Schuller, “Towards Conditional Adversarial Training for Predicting Emotions from Speech,” in Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Calgary, Canada, April 2018, pp.6822-6826  [link]  PPT
  • S. Hantke, N. Cummins, and B. Schuller, “What is my dog trying to tell me? The automatic recognition of the context and perceived emotion of dog barks,” in Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Calgary, Canada, April 2018, pp. 5134-5138.  [link]  [poster]
  • S. Amiriparian, S. Julka, N. Cummins, and B. Schuller, “Deep Convolutional Recurrent Neural Networks for Rare Sound Event Detection,” in Proceedings of the 44. Jahrestagung für Akustik (DAGA), Munich, Germany, March 2018, pp. 1522-1525.
  • M. Schmitt and B. Schuller, “Deep Recurrent Neural Networks for Emotion Recognition in Speech,” in Proceedings of the 44. Jahrestagung für Akustik (DAGA), Munich, Germany, March 2018, pp. 1537-1540.  PPT

 

 

2017

  • K. Qian, Z. Ren, V. Pandit, Z. Yang, Z. Zhang, and B. Schuller, “Wavelets Revisited for the Classification of Acoustic Scenes,” in Proceedings of the Detection and Classification of Acoustic Scenes and Events 2017 IEEE AASP Challenge Workshop (DCASE), Munich, Germany, November 2017. pp. 108-112. PDF  [poster]
  • Z. Ren, V. Pandit, K. Qian, Z. Zhang, Z. Yang, and B. Schuller, “Deep Sequential Image Features on Acoustic Scene Classification,” in Proceedings of the Detection and Classification of Acoustic Scenes and Events 2017 IEEE AASP Challenge Workshop (DCASE), Munich, Germany, November 2017. pp. 113-117.  PDF  [poster]
  • S. Amiriparian, M. Freitag, N. Cummins, and B. Schuller, “Sequence to Sequence Autoencoders for Unsupervised Representation Learning from Audio,” in Proceedings of the Detection and Classification of Acoustic Scenes and Events 2017 IEEE AASP Challenge Workshop (DCASE), Munich, Germany, November 2017. pp. 17-21. PDF PPT
  • S. Amiriparian, N. Cummins, M. Freitag, K. Qian, Z. Ren, V. Pandit, and B. Schuller "The Combined Augsburg / Passau / TUM / ICL System for DCASE 2017", Technical Paper for the Challenge entry at the Detection and Classification of Acoustic Scenes and Events 2017 IEEE AASP Challenge Workshop (DCASE), Munich, Germany, November 2017. 1 page, to appear.  PDF
  • S. Amiriparian, M. Freitag, N. Cummins, and B. Schuller, “Feature Selection in Multimodal Continuous Emotion Prediction,” in Proceedings of the 2nd International Workshop on Automatic Sentiment Analysis in the Wild (WASA 2017) held in conjunction with the 7th biannual Conference on Affective Computing and Intelligent Interaction (ACII), San Antonio, TX, October 2017. pp. 30–37.  [link]  PPT
  • S. Amiriparian, N. Cummins, S. Ottl, M. Gerczuk, and B. Schuller, “Sentiment Analysis Using Image-based Deep Spectrum Features,” in Proceedings of the 2nd International Workshop on Automatic Sentiment Analysis in the Wild (WASA 2017) held in conjunction with the 7th biannual Conference on Affective Computing and Intelligent Interaction (ACII), San Antonio, TX, October 2017. pp. 26–29.  [link]  PPT
  • J. Han, Z. Zhang, M. Schmitt, M. Pantic, and B. Schuller, “From Hard to Soft: Towards more Human-like Emotion Recognition by Modelling the Perception Uncertainty,” in Proceedings of the 25th ACM International Conference on Multimedia (MM), Mountain View, CA, October 2017. pp. 890-897.  [link]  [poster]
  • E. Parada-Cabaleiro, A. Batliner, A. E. Baird, and B. Schuller, “The Perception of Emotion in the Singing Voice,” in Proceedings of the 4th International Digital Libraries for Musicology workshop (DLfM) at the 18th International Society for Music Information Retrieval Conference (ISMIR), Suzhou, China, October 2017, pp. 29-36.  PDF PPT
  • E. Parada-Cabaleiro, A. Batliner, A. E. Baird, and B. Schuller, “The SEILS dataset: Symbolically Encoded Scores in ModernAncient Notation for Computational Musicology,” in Proceedings of the 18th International Society for Music Information Retrieval Conference (ISMIR), Suzhou, China, October 2017. pp. 575-581. PDF  [poster]

Technical Reports

G. Keren, M. Schmitt, T. Kehrenberg, and B. Schuller, “Weakly Supervised One-Shot Detection with Attention Siamese Networks,” arxiv.org, January 2018. 11 pages PDF

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