56 citations · 227 across the 25 of their papers we have counts for
6 papers · 1 filter
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…
A Comparison and Combination of Unsupervised Blind Source Separation Techniques
Christoph Boeddeker, Frederik Rautenberg, Reinhold Haeb-Umbach
Unsupervised blind source separation methods do not require a training phase and thus cannot suffer from a train-test mismatch, which is a common concern in neural network based so…
Convolutive Transfer Function Invariant SDR training criteria for Multi-Channel Reverberant Speech Separation
Christoph Boeddeker, Wangyou Zhang, Tomohiro Nakatani +6
Time-domain training criteria have proven to be very effective for the separation of single-channel non-reverberant speech mixtures. Likewise, mask-based beamforming has shown impr…
Demystifying TasNet: A Dissecting Approach
Jens Heitkaemper, Darius Jakobeit, Christoph Boeddeker +2
In recent years time domain speech separation has excelled over frequency domain separation in single channel scenarios and noise-free environments. In this paper we dissect the ga…
SMS-WSJ: Database, performance measures, and baseline recipe for multi-channel source separation and recognition
Lukas Drude, Jens Heitkaemper, Christoph Boeddeker +1
We present a multi-channel database of overlapping speech for training, evaluation, and detailed analysis of source separation and extraction algorithms: SMS-WSJ -- Spatialized Mul…
Jointly optimal dereverberation and beamforming
Christoph Boeddeker, Tomohiro Nakatani, Keisuke Kinoshita +1
We previously proposed an optimal (in the maximum likelihood sense) convolutional beamformer that can perform simultaneous denoising and dereverberation, and showed its superiority…