| Scent dog identification of samples from COVID-19 patients–a pilot study P Jendrny, C Schulz, F Twele, S Meller, M von Köckritz-Blickwede, ... BMC infectious diseases 20, 1-7, 2020 | 218 | 2020 |
| Threshold Independent Evaluation of Sound Event Detection Scores J Ebbers, R Haeb-Umbach, R Serizel ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | 60 | 2022 |
| Hidden Markov Model Variational Autoencoder for Acoustic Unit Discovery J Ebbers, LD Jahn Heymann, T Glarner, R Haeb-Umbach, B Raj Proc. Interspeech 2017, 488-492, 2017 | 53 | 2017 |
| Scent dog identification of SARS-CoV-2 infections in different body fluids P Jendrny, F Twele, S Meller, C Schulz, M von Köckritz-Blickwede, ... BMC Infectious Diseases 21, 1-14, 2021 | 42 | 2021 |
| Pre-training and self-training for sound event detection in domestic environments J Ebbers, R Haeb-Umbach Detection and Classification of Acoustic Scenes and Events (DCASE) Challenge, 2022 | 28 | 2022 |
| Contrastive Predictive Coding Supported Factorized Variational Autoencoder for Unsupervised Learning of Disentangled Speech Representations J Ebbers, M Kuhlmann, T Cord-Landwehr, R Haeb-Umbach ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 25* | 2021 |
| Self-trained audio tagging and sound event detection in domestic environments J Ebbers, R Haeb-Umbach Proceedings of the 6th Detection and Classification of Acoustic Scenes and …, 2021 | 25 | 2021 |
| Full Bayesian Hidden Markov Model Variational Autoencoder for Acoustic Unit Discovery. T Glarner, P Hanebrink, J Ebbers, R Haeb-Umbach Interspeech, 2688-2692, 2018 | 22 | 2018 |
| Forward-Backward Convolutional Recurrent Neural Networks and Tag-Conditioned Convolutional Neural Networks for Weakly Labeled Semi-supervised Sound Event Detection J Ebbers, R Haeb-Umbach arXiv preprint arXiv:2103.06581, 2021 | 19* | 2021 |
| Convolutional Recurrent Neural Network and Data Augmentation for Audio Tagging with Noisy Labels and Minimal Supervision J Ebbers, R Haeb-Umbach Detection and Classification of Acoustic Scenes and Events 2019 Workshop …, 2019 | 13 | 2019 |
| Privacy-preserving Variational Information Feature Extraction for Domestic Activity Monitoring Versus Speaker Identification A Nelus, J Ebbers, R Haeb-Umbach, R Martin INTERSPEECH 2019, Graz, Austria, 2019 | 13 | 2019 |
| DCASE 2024 Task 4: Sound Event Detection with Heterogeneous Data and Missing Labels S Cornell, J Ebbers, C Douwes, I Martín-Morató, M Harju, A Mesaros, ... arXiv preprint arXiv:2406.08056, 2024 | 12 | 2024 |
| Sound Event Bounding Boxes J Ebbers, FG Germain, G Wichern, JL Roux arXiv preprint arXiv:2406.04212, 2024 | 9 | 2024 |
| Post-Processing Independent Evaluation of Sound Event Detection Systems J Ebbers, R Haeb-Umbach, R Serizel arXiv preprint arXiv:2306.15440, 2023 | 8 | 2023 |
| Weakly Supervised Sound Activity Detection and Event Classification in Acoustic Sensor Networks J Ebbers, L Drude, R Haeb-Umbach, A Brendel, W Kellermann 2019 IEEE 8th International Workshop on Computational Advances in Multi …, 2019 | 8 | 2019 |
| Evaluation of modulation-MFCC features and DNN classification for acoustic event detection J Ebbers, A Nelus, R Martin, R Haeb-Umbach Deutsche Jahrestagung fur Akustik (DAGA), 2018 | 8 | 2018 |
| Sound event detection using metric learning and focal loss for dcase 2021 task 4 G Tian, Y Huang, Z Ye, S Ma, X Wang, H Liu, Y Qian, R Tao, L Yan, ... Tech. Rep., DCASE2021 Challenge, 2021 | 7 | 2021 |
| Investigation into Target Speaking Rate Adaptation for Voice Conversion M Kuhlmann, F Seebauer, J Ebbers, P Wagner, R Haeb-Umbach arXiv preprint arXiv:2209.01978, 2022 | 5 | 2022 |
| Benchmarking Neural Network Architectures for Acoustic Sensor Networks J Ebbers, J Heitkaemper, J Schmalenstroeer, R Haeb-Umbach Speech Communication; 13th ITG-Symposium, 1-5, 2018 | 5 | 2018 |
| Unsupervised learning of a disentangled speech representation for voice conversion T Gburrek, T Glarner, J Ebbers, R Haeb-Umbach, P Wagner Proc. 10th ISCA Speech Synthesis Workshop, 81-86, 2019 | 4 | 2019 |
