Rautenberg, F., Kuhlmann, M., Ebbers, J., Wiechmann, J., Seebauer, F., Wagner, P., &; Haeb-Umbach, R. (2023). Speech Disentanglement for Analysis and Modification of Acoustic and Perceptual Speaker Characteristics. Fortschritte Der Akustik - DAGA 2023, 1409–1412.
LibreCat: /record/44849

Kuhlmann, M., Seebauer, F., Ebbers, J., Wagner, P., &; Haeb-Umbach, R. (2022). Investigation into Target Speaking Rate Adaptation for Voice Conversion. Interspeech 2022.https://doi.org/10.21437/interspeech.2022-10740 
LibreCat: /record/33857
DOI: 10.21437/interspeech.2022-10740

Ebbers, J., Haeb-Umbach, R., &; Serizel, R. (2022). Threshold Independent Evaluation of Sound Event Detection Scores. Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
LibreCat: /record/34072

Ebbers, J., Kuhlmann, M., Cord-Landwehr, T., &; Haeb-Umbach, R. (2021). Contrastive Predictive Coding Supported Factorized Variational Autoencoder for Unsupervised Learning of Disentangled Speech Representations. Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 3860–3864.
LibreCat: /record/29304

Ebbers, J., &; Haeb-Umbach, R. (2021). Self-Trained Audio Tagging and Sound Event Detection in Domestic Environments. Proceedings of the 6th Detection and Classification of Acoustic Scenes and Events 2021 Workshop (DCA), 226–230.
LibreCat: /record/29308

Ebbers, J., Keyser, M. C., &; Haeb-Umbach, R. (2021). Adapting Sound Recognition to A New Environment Via Self-Training. Proceedings of the 29th European Signal Processing Conference (EUSIPCO), 1135–1139.
LibreCat: /record/29306

Ebbers, J., &; Haeb-Umbach, R. (2020). Forward-Backward Convolutional Recurrent Neural Networks and Tag-Conditioned Convolutional Neural Networks for Weakly Labeled Semi-Supervised Sound Event Detection. Proceedings of the Detection and Classification of Acoustic Scenes and Events 2020 Workshop (DCA).
LibreCat: /record/20753

Gburrek, T., Glarner, T., Ebbers, J., Haeb-Umbach, R., &; Wagner, P. (2019). Unsupervised Learning of a Disentangled Speech Representation for Voice Conversion. Proc. 10th ISCA Speech Synthesis Workshop, 81–86.https://doi.org/10.21437/SSW.2019-15 
LibreCat: /record/15237
DOI: 10.21437/SSW.2019-15

Ebbers, J., &; Haeb-Umbach, R. (2019). Convolutional Recurrent Neural Network and Data Augmentation for Audio Tagging with Noisy Labels and Minimal Supervision. DCA Workshop, New York, USA.
LibreCat: /record/15794

Ebbers, J., Drude, L., Haeb-Umbach, R., Brendel, A., &; Kellermann, W. (2019). Weakly Supervised Sound Activity Detection and Event Classification in Acoustic Sensor Networks. CAMSAP 2019, Guadeloupe, West Indies.
LibreCat: /record/15796

Nelus, A., Ebbers, J., Haeb-Umbach, R., &; Martin, R. (2019). Privacy-preserving Variational Information Feature Extraction for Domestic Activity Monitoring Versus Speaker Identification. INTERSPEECH 2019, Graz, Austria.
LibreCat: /record/15792

Ebbers, J., Nelus, A., Martin, R., &; Haeb-Umbach, R. (2018). Evaluation of Modulation-MFCC Features and DNN Classification for Acoustic Event Detection. In DAGA 2018, München.
LibreCat: /record/11760

Glarner, T., Hanebrink, P., Ebbers, J., &; Haeb-Umbach, R. (2018). Full Bayesian Hidden Markov Model Variational Autoencoder for Acoustic Unit Discovery. INTERSPEECH 2018, Hyderabad, India.
LibreCat: /record/11907

Ebbers, J., Heitkaemper, J., Schmalenstroeer, J., &; Haeb-Umbach, R. (2018). Benchmarking Neural Network Architectures for Acoustic Sensor Networks. ITG 2018, Oldenburg, Germany.
LibreCat: /record/11836

Ebbers, J., Heymann, J., Drude, L., Glarner, T., Haeb-Umbach, R., &; Raj, B. (2017). Hidden Markov Model Variational Autoencoder for Acoustic Unit Discovery. INTERSPEECH 2017, Stockholm, Schweden.
LibreCat: /record/11759