32 citations · 159 across the 28 of their papers we have counts for
6 papers · 1 filter
Block Coordinate Descent Algorithms for Auxiliary-Function-Based Independent Vector Extraction
Rintaro Ikeshita, Tomohiro Nakatani, Shoko Araki
In this paper, we address the problem of extracting all super-Gaussian source signals from a linear mixture in which (i) the number of super-Gaussian sources is less than that…
Listen to What You Want: Neural Network-based Universal Sound Selector
Tsubasa Ochiai, Marc Delcroix, Yuma Koizumi +3
Being able to control the acoustic events (AEs) to which we want to listen would allow the development of more controllable hearable devices. This paper addresses the AE sound sele…
Cognitive-driven convolutional beamforming using EEG-based auditory attention decoding
Ali Aroudi, Marc Delcroix, Tomohiro Nakatani +3
The performance of speech enhancement algorithms in a multi-speaker scenario depends on correctly identifying the target speaker to be enhanced. Auditory attention decoding (AAD) m…
Tackling real noisy reverberant meetings with all-neural source separation, counting, and diarization system
Keisuke Kinoshita, Marc Delcroix, Shoko Araki +1
Automatic meeting analysis is an essential fundamental technology required to let, e.g. smart devices follow and respond to our conversations. To achieve an optimal automatic meeti…
Overdetermined independent vector analysis
Rintaro Ikeshita, Tomohiro Nakatani, Shoko Araki
We address the convolutive blind source separation problem for the (over-)determined case where (i) the number of nonstationary target-sources is less than that of microphones…
Improving speaker discrimination of target speech extraction with time-domain SpeakerBeam
Marc Delcroix, Tsubasa Ochiai, Katerina Zmolikova +4
Target speech extraction, which extracts a single target source in a mixture given clues about the target speaker, has attracted increasing attention. We have recently proposed Spe…