69 citations · 83 across the 7 of their papers we have counts for
9 papers
Subspace Track-before-Detect for Passive Multi-Target Tracking with Unknown Emitted Signals
Nobutaka Ito, Yoshiaki Bando
Passive multi-target tracking (MTT) aims to infer the time-varying kinematic and activity states of an unknown number of sources that emit unknown and possibly nonstationary signal…
Gaussian Process Regression of Steering Vectors With Physics-Aware Deep Composite Kernels for Augmented Listening
Diego Di Carlo, Shoichi Koyama, Nugraha Aditya Arie +3
This paper investigates continuous representations of steering vectors over frequency and microphone/source positions for augmented listening (e.g., spatial filtering and binaural…
SHAMaNS: Sound Localization with Hybrid Alpha-Stable Spatial Measure and Neural Steerer
Diego Di Carlo, Mathieu Fontaine, Aditya Arie Nugraha +2
This paper describes a sound source localization (SSL) technique that combines an -stable model for the observed signal with a neural network-based approach for modeling steerin…
Run-Time Adaptation of Neural Beamforming for Robust Speech Dereverberation and Denoising
Yoto Fujita, Aditya Arie Nugraha, Diego Di Carlo +3
This paper describes speech enhancement for realtime automatic speech recognition (ASR) in real environments. A standard approach to this task is to use neural beamforming that can…
Generalized Fast Multichannel Nonnegative Matrix Factorization Based on Gaussian Scale Mixtures for Blind Source Separation
Mathieu Fontaine, Kouhei Sekiguchi, Aditya Nugraha +2
This paper describes heavy-tailed extensions of a state-of-the-art versatile blind source separation method called fast multichannel nonnegative matrix factorization (FastMNMF) fro…
Self-supervised Neural Audio-Visual Sound Source Localization via Probabilistic Spatial Modeling
Yoshiki Masuyama, Yoshiaki Bando, Kohei Yatabe +3
Detecting sound source objects within visual observation is important for autonomous robots to comprehend surrounding environments. Since sounding objects have a large variety with…