On behalf of the organising committee, I am pleased to announce the release of the development dataset for the IEEE-AASP Challenge on Acoustic Source Localization and Tracking (LOCATA).
The aim of this challenge is to provide researchers in the field of acoustic source localization and tracking the opportunity to benchmark their...
Open Access:
IEEE Transactions on Signal Processing
Authors:
Christine Evers and Patrick A. Naylor
Abstract:
In many applications, sensors that map the positions of objects in unknown environments are installed on dynamic platforms. As measurements are relative to the observer's sensors, scene mapping requires accurate knowledge of the observer state. However, in practice, observer reports...
IEEE Xplore Access:
Proc. European Signal Processing Conference (EUSIPCO)
Authors:
Constantinos Papayannis, Christine Evers and Patrick A. Naylor
Abstract:
Acoustic channels are typically described by their Acoustic Impulse Response (AIR) as a Moving Average (MA) process. Such AIRs are often considered in terms of their early and late parts, describing discrete reflections and the diffuse...
The slides for my keynote speech on "Bayesian Learning for Robot Audition" at HSCMA 2017 are now online on the website of the IEEE Audio and Acoustic Signal Processing Technical Committee....
We received the best paper award at the IEEE Fifth Joint Workshop on Hands-free Speech Communication and Microphone Arrays, San Francisco, USA, 1-3 March 2017, for our paper on "Audio-visual Tracking by Density Approximation in a Sequential Bayesian Filtering Framework"....
IEEE Xplore Access:
in Proc. IEEE Intl. Conf. on Acoustics, Speech and Signal Processing (ICASSP)
Authors:
C. Papayiannis, C. Evers, and P. A. Naylor
Abstract:
Several speech processing and audio data-mining applications rely on a description of the acoustic environment as a feature vector for classification. The discriminative properties of the feature domain play a...