Loose Coupling of Spectral and Spatial Models for Multi-Channel Diarization and Enhancement of Meetings in Dynamic Environments Meise, Adrian Tobias Cord-Landwehr, Tobias Boeddeker, Christoph Delcroix, Marc Nakatani, Tomohiro Haeb-Umbach, Reinhold mixture models meeting processing diarization source separation Sound capture by microphone arrays opens the possibility to exploit spatial, in addition to spectral, information for diarization and signal enhancement, two important tasks in meeting transcription. However, there is no one-to-one mapping of positions in space to speakers if speakers move. Here, we address this by proposing a novel joint spatial and spectral mixture model, whose two submodels are loosely coupled by modeling the relationship between speaker and position index probabilistically. Thus, spatial and spectral information can be jointly exploited, while at the same time allowing for speakers speaking from different positions. Experiments on the LibriCSS data set with simulated speaker position changes show great improvements over tightly coupled subsystems. IEEE 2026 info:eu-repo/semantics/conferenceObject doc-type:conferenceObject text http://purl.org/coar/resource_type/c_5794 https://ris.uni-paderborn.de/record/65606 Meise AT, Cord-Landwehr T, Boeddeker C, Delcroix M, Nakatani T, Haeb-Umbach R. Loose Coupling of Spectral and Spatial Models for Multi-Channel Diarization and Enhancement of Meetings in Dynamic Environments. In: <i>ICASSP 2026 - 2026 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)</i>. IEEE; 2026. doi:<a href="https://doi.org/10.1109/icassp55912.2026.11463540">10.1109/icassp55912.2026.11463540</a> eng info:eu-repo/semantics/altIdentifier/doi/10.1109/icassp55912.2026.11463540 info:eu-repo/semantics/altIdentifier/arxiv/https://arxiv.org/abs/2601.16077 info:eu-repo/semantics/openAccess