A new approach to the separation of speech from speech-in-noise mixtures is the use of time-
frequency (TF) masking. Originated in the field of computational auditory scene analysis, TF …

Independent component analysis (ICA) is a signal processing technique used for separating
statistically independent and non-Gaussian mixed signals. It is widely used in different areas …

Acoustic sensing from a multi-rotor drone is heavily degraded by the strong ego-noise
produced by the rotating motors and propellers. To address this problem, we propose a …

In this paper, we have proposed a low-cost self-localization method which uses 4 elements
of microphones, wheel rotation and sound sources as beacons, whose absolute location …

This paper addresses the online calibration of an asynchronous microphone array for
robots. Conventional microphone array technologies require a lot of measurements of …

Autonomous systems (ASs) operating in real-world environments are exposed to a plurality
and diversity of sounds that carry a wealth of information for perception in cognitive dynamic …

A signal processing apparatus includes: a learning processing unit that finds a separating
matrix for separating mixed signals in which outputs from a plurality of sound sources are …

This paper addresses ego-motion noise suppression for a robot. Many methods use motion
information such as position, velocity and acceleration of each joint to infer ego-motion …

Independent component analysis (ICA) is a signal processing technique used for blind
source separation of the mixed received signals. In wireless communication, it is widely …

Independent component analysis (ICA) is a technique of blind source separation (BSS) used
for separation of the mixed received signals. ICA algorithms are classified into adaptive and …