1 citations · 2 across the 2 of their papers we have counts for
5 papers · 1 filter
The LOCATA Challenge: Acoustic Source Localization and Tracking
Christine Evers, Heinrich Loellmann, Heinrich Mellmann +4
The ability to localize and track acoustic events is a fundamental prerequisite for equipping machines with the ability to be aware of and engage with humans in their surrounding e…
Detecting Sound-Absorbing Materials in a Room from a Single Impulse Response using a CRNN
Constantinos Papayiannis, Christine Evers, Patrick A. Naylor
The materials of surfaces in a room play an important room in shaping the auditory experience within them. Different materials absorb energy at different levels. The level of absor…
Data Augmentation of Room Classifiers using Generative Adversarial Networks
Constantinos Papayiannis, Christine Evers, Patrick A. Naylor
The classification of acoustic environments allows for machines to better understand the auditory world around them. The use of deep learning in order to teach machines to discrimi…
End-to-End Classification of Reverberant Rooms using DNNs
Constantinos Papayiannis, Christine Evers, Patrick A. Naylor
Reverberation is present in our workplaces, our homes, concert halls and theatres. This paper investigates how deep learning can use the effect of reverberation on speech to classi…
Proceedings of the LOCATA Challenge Workshop -- a satellite event of IWAENC 2018
Heinrich W. Loellmann, Christine Evers, Alexander Schmidt +3
Algorithms for acoustic source localization and tracking provide estimates of the positional information about active sound sources in acoustic environments and are essential for a…