Sound Source Separation Adaptable to Environmental Changes for Robot Audition

Real-time sound source localization and separation for robot audition

Robot audition in the real world should cope with environment noises and reverberation and motor noises caused by the robot’s own movements. This paper presents the active direction-pass filter (ADPF) to separate sounds originating from the specified direction with a pair of microphones. The ADPF is implemented by hierarchical integration of visual and auditory processing with hypothetical reas...

Blind source separation for robot audition using fixed HRTF beamforming

In this article, we present a two-stage blind source separation (BSS) algorithm for robot audition. The first stage consists in a fixed beamforming preprocessing to reduce the reverberation and the environmental noise. Since we are in a robot audition context, the manifold of the sensor array in this case is hard to model due to the presence of the head of the robot, so we use pre-measured head...

Applying scattering theory to robot audition system: robust sound source localization and extraction

Robot audition by its own ears (microphones) is essential for natural human-robot communication and interface. Since a microphone is embedded in the head of a robot, the head-related transfer function (HRTF) plays an important role in sound source localization and extraction. Usually, from binaural input, the interaural phase difference (IPD) and interaural intensity difference (IID) are calcul...

Blind Source Separation for Robot Audition Using Fixed Beamforming with HRTFs

We present a two stage blind source separation (BSS) algorithm for robot audition. The algorithm is based on a beamforming preprocessing and a BSS algorithm using a sparsity separation criterion. Before the BSS step, we filter the sensors outputs by beamforming filters to reduce the reverberation and the environmental noise. As we are in a robot audition context, the manifold of the sensor arra...

Separation of Sound Sources: a Machine Audition Perspective