Rautenberg F, Kuhlmann M, Ebbers J, et al. Speech Disentanglement for Analysis and Modification of Acoustic and Perceptual Speaker Characteristics. In: Fortschritte Der Akustik - DAGA 2023. ; 2023:1409-1412.

Kuhlmann M, Seebauer F, Ebbers J, Wagner P, Haeb-Umbach R. Investigation into Target Speaking Rate Adaptation for Voice Conversion. In: Interspeech 2022. ISCA; 2022. doi:10.21437/interspeech.2022-10740

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

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

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

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

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

Gburrek T, Glarner T, Ebbers J, Haeb-Umbach R, Wagner P. Unsupervised Learning of a Disentangled Speech Representation for Voice Conversion. In: Proc. 10th ISCA Speech Synthesis Workshop. ; 2019:81-86. doi:10.21437/SSW.2019-15

Ebbers J, Haeb-Umbach R. Convolutional Recurrent Neural Network and Data Augmentation for Audio Tagging with Noisy Labels and Minimal Supervision. In: DCA Workshop, New York, USA. ; 2019.

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

Nelus A, Ebbers J, Haeb-Umbach R, Martin R. Privacy-preserving Variational Information Feature Extraction for Domestic Activity Monitoring Versus Speaker Identification. In: INTERSPEECH 2019, Graz, Austria. ; 2019.

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

Glarner T, Hanebrink P, Ebbers J, Haeb-Umbach R. Full Bayesian Hidden Markov Model Variational Autoencoder for Acoustic Unit Discovery. In: INTERSPEECH 2018, Hyderabad, India. ; 2018.

Ebbers J, Heitkaemper J, Schmalenstroeer J, Haeb-Umbach R. Benchmarking Neural Network Architectures for Acoustic Sensor Networks. In: ITG 2018, Oldenburg, Germany. ; 2018.

Ebbers J, Heymann J, Drude L, Glarner T, Haeb-Umbach R, Raj B. Hidden Markov Model Variational Autoencoder for Acoustic Unit Discovery. In: INTERSPEECH 2017, Stockholm, Schweden. ; 2017.