32 citations · 159 across the 28 of their papers we have counts for
9 papers · 1 filter
Switching Independent Vector Analysis and Its Extension to Blind and Spatially Guided Convolutional Beamforming Algorithms
Tomohiro Nakatani, Rintaro Ikeshita, Keisuke Kinoshita +3
This paper develops a framework that can perform denoising, dereverberation, and source separation accurately by using a relatively small number of microphones. It has been empiric…
Blind and neural network-guided convolutional beamformer for joint denoising, dereverberation, and source separation
Tomohiro Nakatani, Rintaro Ikeshita, Keisuke Kinoshita +2
This paper proposes an approach for optimizing a Convolutional BeamFormer (CBF) that can jointly perform denoising (DN), dereverberation (DR), and source separation (SS). First, we…
Few-shot learning of new sound classes for target sound extraction
Marc Delcroix, Jorge Bennasar Vázquez, Tsubasa Ochiai +2
Target sound extraction consists of extracting the sound of a target acoustic event (AE) class from a mixture of AE sounds. It can be realized using a neural network that extracts…
PILOT: Introducing Transformers for Probabilistic Sound Event Localization
Christopher Schymura, Benedikt Bönninghoff, Tsubasa Ochiai +5
Sound event localization aims at estimating the positions of sound sources in the environment with respect to an acoustic receiver (e.g. a microphone array). Recent advances in thi…
Comparison of remote experiments using crowdsourcing and laboratory experiments on speech intelligibility
Ayako Yamamoto, Toshio Irino, Kenichi Arai +4
Many subjective experiments have been performed to develop objective speech intelligibility measures, but the novel coronavirus outbreak has made it very difficult to conduct exper…
Exploiting Attention-based Sequence-to-Sequence Architectures for Sound Event Localization
Christopher Schymura, Tsubasa Ochiai, Marc Delcroix +4
Sound event localization frameworks based on deep neural networks have shown increased robustness with respect to reverberation and noise in comparison to classical parametric appr…
Data Fusion for Audiovisual Speaker Localization: Extending Dynamic Stream Weights to the Spatial Domain
Julio Wissing, Benedikt Boenninghoff, Dorothea Kolossa +6
Estimating the positions of multiple speakers can be helpful for tasks like automatic speech recognition or speaker diarization. Both applications benefit from a known speaker posi…
Multimodal Attention Fusion for Target Speaker Extraction
Hiroshi Sato, Tsubasa Ochiai, Keisuke Kinoshita +3
Target speaker extraction, which aims at extracting a target speaker's voice from a mixture of voices using audio, visual or locational clues, has received much interest. Recently…
Neural Network-based Virtual Microphone Estimator
Tsubasa Ochiai, Marc Delcroix, Tomohiro Nakatani +3
Developing microphone array technologies for a small number of microphones is important due to the constraints of many devices. One direction to address this situation consists of…