56 citations · 160 across the 12 of their papers we have counts for
18 papers
Microphone Array Signal Processing and Deep Learning for Speech Enhancement
Reinhold Haeb-Umbach, Tomohiro Nakatani, Marc Delcroix +2
Multi-channel acoustic signal processing is a well-established and powerful tool to exploit the spatial diversity between a target signal and non-target or noise sources for signal…
Simultaneous Diarization and Separation of Meetings through the Integration of Statistical Mixture Models
Tobias Cord-Landwehr, Christoph Boeddeker, Reinhold Haeb-Umbach
We propose an approach for simultaneous diarization and separation of meeting data. It consists of a complex Angular Central Gaussian Mixture Model (cACGMM) for speech source separ…
Reverberation as Supervision for Speech Separation
Rohith Aralikatti, Christoph Boeddeker, Gordon Wichern +2
This paper proposes reverberation as supervision (RAS), a novel unsupervised loss function for single-channel reverberant speech separation. Prior methods for unsupervised separati…
MMS-MSG: A Multi-purpose Multi-Speaker Mixture Signal Generator
Tobias Cord-Landwehr, Thilo von Neumann, Christoph Boeddeker +1
The scope of speech enhancement has changed from a monolithic view of single, independent tasks, to a joint processing of complex conversational speech recordings. Training and eva…
A Meeting Transcription System for an Ad-Hoc Acoustic Sensor Network
Tobias Gburrek, Christoph Boeddeker, Thilo von Neumann +3
We propose a system that transcribes the conversation of a typical meeting scenario that is captured by a set of initially unsynchronized microphone arrays at unknown positions. It…
An Initialization Scheme for Meeting Separation with Spatial Mixture Models
Christoph Boeddeker, Tobias Cord-Landwehr, Thilo von Neumann +1
Spatial mixture model (SMM) supported acoustic beamforming has been extensively used for the separation of simultaneously active speakers. However, it has hardly been considered fo…