| All-neural online source separation, counting, and diarization for meeting analysis T Von Neumann, K Kinoshita, M Delcroix, S Araki, T Nakatani, ... ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019 | 82 | 2019 |
| Multi-talker ASR for an unknown number of sources: Joint training of source counting, separation and ASR T von Neumann, C Boeddeker, L Drude, K Kinoshita, M Delcroix, ... arXiv preprint arXiv:2006.02786, 2020 | 31 | 2020 |
| Deep attractor networks for speaker re-identification and blind source separation L Drude, T von Neumann, R Haeb-Umbach 2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018 | 29 | 2018 |
| End-to-end training of time domain audio separation and recognition T von Neumann, K Kinoshita, L Drude, C Boeddeker, M Delcroix, ... ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 28 | 2020 |
| Graph-PIT: Generalized permutation invariant training for continuous separation of arbitrary numbers of speakers T von Neumann, K Kinoshita, C Boeddeker, M Delcroix, R Haeb-Umbach arXiv preprint arXiv:2107.14446, 2021 | 16 | 2021 |
| Monaural source separation: From anechoic to reverberant environments T Cord-Landwehr, C Boeddeker, T Von Neumann, C Zorilă, R Doddipatla, ... 2022 International Workshop on Acoustic Signal Enhancement (IWAENC), 1-5, 2022 | 10 | 2022 |
| SA-SDR: A novel loss function for separation of meeting style data T von Neumann, K Kinoshita, C Boeddeker, M Delcroix, R Haeb-Umbach ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | 8 | 2022 |
| Multi-path RNN for hierarchical modeling of long sequential data and its application to speaker stream separation K Kinoshita, T von Neumann, M Delcroix, T Nakatani, R Haeb-Umbach arXiv preprint arXiv:2006.13579, 2020 | 8 | 2020 |
| Speeding up permutation invariant training for source separation T von Neumann, C Boeddeker, K Kinoshita, M Delcroix, R Haeb-Umbach Speech Communication; 14th ITG Conference, 1-5, 2021 | 6 | 2021 |
| An initialization scheme for meeting separation with spatial mixture models C Boeddeker, T Cord-Landwehr, T von Neumann, R Haeb-Umbach arXiv preprint arXiv:2204.01338, 2022 | 3 | 2022 |
| Estimation device, learning device, estimation method, learning method, and recording medium K Kinoshita, M Delcroix, T Nakatani, S Araki, L Drude, TC Von Neumann US Patent 11,456,003, 2022 | 2 | 2022 |
| A meeting transcription system for an ad-hoc acoustic sensor network T Gburrek, C Boeddeker, T von Neumann, T Cord-Landwehr, ... arXiv preprint arXiv:2205.00944, 2022 | 2 | 2022 |
| On Word Error Rate Definitions and their Efficient Computation for Multi-Speaker Speech Recognition Systems T von Neumann, C Boeddeker, K Kinoshita, M Delcroix, R Haeb-Umbach arXiv preprint arXiv:2211.16112, 2022 | 1 | 2022 |
| MMS-MSG: A Multi-Purpose Multi-Speaker Mixture Signal Generator T Cord-Landwehr, T Von Neumann, C Boeddeker, R Haeb-Umbach 2022 International Workshop on Acoustic Signal Enhancement (IWAENC), 1-5, 2022 | 1 | 2022 |
| Utterance-by-utterance overlap-aware neural diarization with Graph-PIT K Kinoshita, T von Neumann, M Delcroix, C Boeddeker, R Haeb-Umbach arXiv preprint arXiv:2207.13888, 2022 | 1 | 2022 |
| Segment-Less Continuous Speech Separation of Meetings: Training and Evaluation Criteria T von Neumann, K Kinoshita, C Boeddeker, M Delcroix, R Haeb-Umbach IEEE/ACM Transactions on Audio, Speech, and Language Processing 31, 576-589, 2022 | | 2022 |
Reinhold Haeb-UmbachProfessor of Communications Engineering, University of PaderbornAdresse e-mail validée de nt.uni-paderborn.de
