The "cocktail party problem" has always been a challenging problem to solve and many blind source separation algorithms have been proposed as solutions. This problem has mainly been discussed for non-moving sound sources but it still remains for moving sound sources and high acoustic reverberations. The ability to localise and track multiple moving speakers is a pre-requisite to solving this problem. The aim of this paper is to show that a combination of Degenerate Unmixing Estimation Technique and a Cardinality Balanced Multitarget Multi-Bernoulli Filter provides a viable way to track multiple sound sources and subsequently address the problem of sound separation for moving targets
In this thesis, a novel approach is proposed for multi-speaker tracking by integrating audio and vis...
International audienceWe address the problem of online localization and tracking of multiple moving ...
A new method is presented for integration of audio and visual information in multiple target trackin...
In a 'conference room scenario', the number of speech sources are not known a priori and the number ...
In this paper we propose a new solution to the problem of tracking multiple speakers from multiple m...
Blind audio source separation (BASS) is a fascinating problem that has been tackled from many differ...
Audio-visual tracking of multiple speakers requires to estimate the state (e.g. velocity and locatio...
© 2017 IEEE. In this paper we propose a new solution to the problem of tracking multiple speakers fr...
An improvement is proposed in the audio-visual approach to solve the problem of source separation of...
Particle Filter-based Acoustic Source Tracking algorithms track (online and in real-time) the positi...
In this paper we deal with the problem of localizing and tracking multiple acoustic sources by means...
A novel multimodal solution is proposed to solve the problem of blind source separation (BSS) of mov...
In this paper, we give an overview of the background for, the ideas behind, and the challenges to be...
A random finite set-based sequential Monte–Carlo tracking method is proposed to track multiple acous...
The particle filter (PF) algorithm is appropriate to solve the problem of speaker tracking in a reve...
In this thesis, a novel approach is proposed for multi-speaker tracking by integrating audio and vis...
International audienceWe address the problem of online localization and tracking of multiple moving ...
A new method is presented for integration of audio and visual information in multiple target trackin...
In a 'conference room scenario', the number of speech sources are not known a priori and the number ...
In this paper we propose a new solution to the problem of tracking multiple speakers from multiple m...
Blind audio source separation (BASS) is a fascinating problem that has been tackled from many differ...
Audio-visual tracking of multiple speakers requires to estimate the state (e.g. velocity and locatio...
© 2017 IEEE. In this paper we propose a new solution to the problem of tracking multiple speakers fr...
An improvement is proposed in the audio-visual approach to solve the problem of source separation of...
Particle Filter-based Acoustic Source Tracking algorithms track (online and in real-time) the positi...
In this paper we deal with the problem of localizing and tracking multiple acoustic sources by means...
A novel multimodal solution is proposed to solve the problem of blind source separation (BSS) of mov...
In this paper, we give an overview of the background for, the ideas behind, and the challenges to be...
A random finite set-based sequential Monte–Carlo tracking method is proposed to track multiple acous...
The particle filter (PF) algorithm is appropriate to solve the problem of speaker tracking in a reve...
In this thesis, a novel approach is proposed for multi-speaker tracking by integrating audio and vis...
International audienceWe address the problem of online localization and tracking of multiple moving ...
A new method is presented for integration of audio and visual information in multiple target trackin...