C. Boeddeker, A. S. Subramanian, G. Wichern, R. Haeb-Umbach, and J. Le Roux, “TS-SEP: Joint Diarization and Separation Conditioned on Estimated Speaker Embeddings,”10.1109/taslp.2024.3350887__IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 32, pp. 1185–1197, 2024, doi:10.1109/taslp.2024.3350887 .

T. Cord-Landwehr, C. Boeddeker, C. Zoril, R. Doddipatla, and R. Haeb-Umbach, “Geodesic Interpolation of Frame-Wise Speaker Embeddings for the Diarization of Meeting Scenarios,”10.1109/icassp48485.2024.10445911__presented at the 2024 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Seoul, 2024, doi:10.1109/icassp48485.2024.10445911 .

T. Cord-Landwehr, C. Boeddeker, C. Zoril, R. Doddipatla, and R. Haeb-Umbach, “Frame-Wise and Overlap-Robust Speaker Embeddings for Meeting Diarization,”10.1109/icassp49357.2023.10095370__presented at the 2023 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Rhodes, 2023, doi:10.1109/icassp49357.2023.10095370 .

T. Cord-Landwehr, C. Boeddeker, C. Zoril, R. Doddipatla, and R. Haeb-Umbach, “A Teacher-Student Approach for Extracting Informative Speaker Embeddings From Speech Mixtures,”10.21437/interspeech.2023-1379__2023, doi:10.21437/interspeech.2023-1379 .

R. Aralikatti, C. Boeddeker, G. Wichern, A. Subramanian, and J. Le Roux, “Reverberation as Supervision For Speech Separation,”10.1109/icassp49357.2023.10095022__2023, doi:10.1109/icassp49357.2023.10095022 .

S. Berger, P. Vieting, C. Boeddeker, R. Schlüter, and R. Haeb-Umbach, “Mixture Encoder for Joint Speech Separation and Recognition,”10.21437/interspeech.2023-1815__2023, doi:10.21437/interspeech.2023-1815 .

T. von Neumann, K. Kinoshita, C. Boeddeker, M. Delcroix, and R. Haeb-Umbach, “Segment-Less Continuous Speech Separation of Meetings: Training and Evaluation Criteria,”10.1109/taslp.2022.3228629__IEEE/ACM Transactions on Audio, Speech, and Language Processing, vol. 31, pp. 576–589, 2023, doi:10.1109/taslp.2022.3228629 .

T. von Neumann, C. Boeddeker, K. Kinoshita, M. Delcroix, and R. Haeb-Umbach, “On Word Error Rate Definitions and Their Efficient Computation for Multi-Speaker Speech Recognition Systems,”10.1109/icassp49357.2023.10094784__2023, doi:10.1109/icassp49357.2023.10094784 .

T. von Neumann, C. Boeddeker, M. Delcroix, and R. Haeb-Umbach, “MeetEval: A Toolkit for Computation of Word Error Rates for Meeting Transcription Systems,” presented at the CHiME 2023 Workshop on Speech Processing in Everyday Environments, Dublin, 2023.

C. Boeddeker, T. Cord-Landwehr, T. von Neumann, and R. Haeb-Umbach, “Multi-stage diarization refinement for the CHiME-7 DASR scenario,”10.21437/chime.2023-10__2023, doi:10.21437/chime.2023-10 .

W. Zhang, X. Chang, C. Boeddeker, T. Nakatani, S. Watanabe, and Y. Qian, “End-to-End Dereverberation, Beamforming, and Speech Recognition in A Cocktail Party,”10.1109/TASLP.2022.3209942__IEEE/ACM Transactions on Audio, Speech, and Language Processing, 2022, doi:10.1109/TASLP.2022.3209942 .

C. Boeddeker, T. Cord-Landwehr, T. von Neumann, and R. Haeb-Umbach, “An Initialization Scheme for Meeting Separation with Spatial Mixture Models,”10.21437/interspeech.2022-10929__2022, doi:10.21437/interspeech.2022-10929 .

K. Kinoshita, T. von Neumann, M. Delcroix, C. Boeddeker, and R. Haeb-Umbach, “Utterance-by-utterance overlap-aware neural diarization with Graph-PIT,”10.21437/Interspeech.2022-11408__in Proc. Interspeech 2022, 2022, pp. 1486–1490, doi:10.21437/Interspeech.2022-11408 .

T. von Neumann, K. Kinoshita, C. Boeddeker, M. Delcroix, and R. Haeb-Umbach, “SA-SDR: A Novel Loss Function for Separation of Meeting Style Data,”10.1109/icassp43922.2022.9746757__2022, doi:10.1109/icassp43922.2022.9746757 .

T. Cord-Landwehr, T. von Neumann, C. Boeddeker, and R. Haeb-Umbach, “MMS-MSG: A Multi-purpose Multi-Speaker Mixture Signal Generator,” presented at the 2022 International Workshop on Acoustic Signal Enhancement (IWAENC), Bamberg, 2022.

T. Cord-Landwehr, C. Boeddeker, T. von Neumann, C. Zorila, R. Doddipatla, and R. Haeb-Umbach, “Monaural source separation: From anechoic to reverberant environments,” presented at the 2022 International Workshop on Acoustic Signal Enhancement (IWAENC), 2022.

T. Gburrek, C. Boeddeker, T. von Neumann, T. Cord-Landwehr, J. Schmalenstroeer, and R. Haeb-Umbach, A Meeting Transcription System for an Ad-Hoc Acoustic Sensor Network. arXiv, 2022.

W. Zhang et al., “End-to-End Dereverberation, Beamforming, and Speech Recognition with Improved Numerical Stability and Advanced Frontend,”10.1109/icassp39728.2021.9414464__2021, doi:10.1109/icassp39728.2021.9414464 .

C. Li et al., “ESPnet-SE: End-To-End Speech Enhancement and Separation Toolkit Designed for ASR Integration,”10.1109/slt48900.2021.9383615__2021, doi:10.1109/slt48900.2021.9383615 .

C. Li et al., “Dual-Path RNN for Long Recording Speech Separation,”10.1109/slt48900.2021.9383514__2021, doi:10.1109/slt48900.2021.9383514 .