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2020 – today
- 2024
[i8]Janek Ebbers, François G. Germain, Gordon Wichern, Jonathan Le Roux:
Sound Event Bounding Boxes. CoRR abs/2406.04212 (2024)- [i7]Samuele Cornell, Janek Ebbers, Constance Douwes, Irene Martín-Morató, Manu Harju, Annamaria Mesaros, Romain Serizel:
DCASE 2024 Task 4: Sound Event Detection with Heterogeneous Data and Missing Labels. CoRR abs/2406.08056 (2024) - [i6]Kohei Saijo, Janek Ebbers, François G. Germain, Sameer Khurana, Gordon Wichern, Jonathan Le Roux:
Leveraging Audio-Only Data for Text-Queried Target Sound Extraction. CoRR abs/2409.13152 (2024) - 2023
- [i5]Janek Ebbers, Reinhold Haeb-Umbach, Romain Serizel:
Post-Processing Independent Evaluation of Sound Event Detection Systems. CoRR abs/2306.15440 (2023) - 2022
- [c13]Janek Ebbers, Reinhold Haeb-Umbach, Romain Serizel:
Threshold Independent Evaluation of Sound Event Detection Scores. ICASSP 2022: 1021-1025 - [c12]Michael Kuhlmann, Fritz Seebauer, Janek Ebbers, Petra Wagner
, Reinhold Haeb-Umbach:
Investigation into Target Speaking Rate Adaptation for Voice Conversion. INTERSPEECH 2022: 4930-4934 - [i4]Janek Ebbers, Romain Serizel, Reinhold Haeb-Umbach:
Threshold Independent Evaluation of Sound Event Detection Scores. CoRR abs/2201.13148 (2022) - 2021
- [c11]Janek Ebbers, Reinhold Haeb-Umbach:
Self-Trained Audio Tagging and Sound Event Detection in Domestic Environments. DCASE 2021: 226-230 - [c10]Janek Ebbers, Moritz Curt Keyser, Reinhold Haeb-Umbach:
Adapting Sound Recognition to A New Environment Via Self-Training. EUSIPCO 2021: 1135-1139 - [c9]Janek Ebbers, Michael Kuhlmann, Tobias Cord-Landwehr, Reinhold Haeb-Umbach:
Contrastive Predictive Coding Supported Factorized Variational Autoencoder For Unsupervised Learning Of Disentangled Speech Representations. ICASSP 2021: 3860-3864 - [i3]Janek Ebbers, Reinhold Haeb-Umbach:
Forward-Backward Convolutional Recurrent Neural Networks and Tag-Conditioned Convolutional Neural Networks for Weakly Labeled Semi-supervised Sound Event Detection. CoRR abs/2103.06581 (2021) - [i2]Thomas Glarner, Janek Ebbers, Reinhold Häb-Umbach:
Voice Conversion Based Speaker Normalization for Acoustic Unit Discovery. CoRR abs/2105.01786 (2021) - 2020
- [c8]Janek Ebbers, Reinhold Haeb-Umbach:
Forward-Backward Convolutional Recurrent Neural Networks and Tag-Conditioned Convolutional Neural Networks for Weakly Labeled Semi-Supervised Sound Event Detection. DCASE 2020: 41-45 - [i1]Janek Ebbers, Michael Kuhlmann, Reinhold Haeb-Umbach:
Adversarial Contrastive Predictive Coding for Unsupervised Learning of Disentangled Representations. CoRR abs/2005.12963 (2020)
2010 – 2019
- 2019
- [c7]Janek Ebbers, Lukas Drude, Reinhold Haeb-Umbach, Andreas Brendel, Walter Kellermann:
Weakly Supervised Sound Activity Detection and Event Classification in Acoustic Sensor Networks. CAMSAP 2019: 301-305 - [c6]Janek Ebbers, Reinhold Häb-Umbach:
Convolutional Recurrent Neural Network and Data Augmentation for Audio Tagging with Noisy Labels and Minimal Supervision. DCASE 2019: 64-68 - [c5]Alexandru Nelus, Janek Ebbers, Reinhold Haeb-Umbach, Rainer Martin:
Privacy-Preserving Variational Information Feature Extraction for Domestic Activity Monitoring versus Speaker Identification. INTERSPEECH 2019: 3710-3714 - [c4]Tobias Gburrek, Thomas Glarner, Janek Ebbers, Reinhold Haeb-Umbach, Petra Wagner:
Unsupervised Learning of a Disentangled Speech Representation for Voice Conversion. SSW 2019: 81-86 - 2018
- [c3]Janek Ebbers, Jens Heitkaemper, Joerg Schmalenstroeer, Reinhold Haeb-Umbach:
Benchmarking Neural Network Architectures for Acoustic Sensor Networks. ITG Symposium on Speech Communication 2018: 1-5 - [c2]Thomas Glarner, Patrick Hanebrink, Janek Ebbers, Reinhold Haeb-Umbach:
Full Bayesian Hidden Markov Model Variational Autoencoder for Acoustic Unit Discovery. INTERSPEECH 2018: 2688-2692 - 2017
- [c1]Janek Ebbers, Jahn Heymann, Lukas Drude, Thomas Glarner, Reinhold Haeb-Umbach, Bhiksha Raj:
Hidden Markov Model Variational Autoencoder for Acoustic Unit Discovery. INTERSPEECH 2017: 488-492
Coauthor Index
aka: Reinhold Haeb-Umbach
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