17 citations · 17 across the 4 of their papers we have counts for
6 papers
Identifying muon rings in VERITAS data using convolutional neural networks trained on images classified with Muon Hunters 2
Kevin Flanagan, John Quinn, Darryl Wright +4
Muons from extensive air showers appear as rings in images taken with imaging atmospheric Cherenkov telescopes, such as VERITAS. These muon-ring images are used for the calibration…
Feature learning for efficient ASR-free keyword spotting in low-resource languages
Ewald van der Westhuizen, Herman Kamper, Raghav Menon +2
We consider feature learning for efficient keyword spotting that can be applied in severely under-resourced settings. The objective is to support humanitarian relief programmes by…
Continental-Scale Building Detection from High Resolution Satellite Imagery
Wojciech Sirko, Sergii Kashubin, Marvin Ritter +7
Identifying the locations and footprints of buildings is vital for many practical and scientific purposes. Such information can be particularly useful in developing regions where a…
Feature exploration for almost zero-resource ASR-free keyword spotting using a multilingual bottleneck extractor and correspondence autoencoders
Raghav Menon, Herman Kamper, Ewald van der Westhuizen +2
We compare features for dynamic time warping (DTW) when used to bootstrap keyword spotting (KWS) in an almost zero-resource setting. Such quickly-deployable systems aim to support…
Automatic Speech Recognition for Humanitarian Applications in Somali
Raghav Menon, Astik Biswas, Armin Saeb +2
We present our first efforts in building an automatic speech recognition system for Somali, an under-resourced language, using 1.57 hrs of annotated speech for acoustic model train…
Fast ASR-free and almost zero-resource keyword spotting using DTW and CNNs for humanitarian monitoring
Raghav Menon, Herman Kamper, John Quinn +1
We use dynamic time warping (DTW) as supervision for training a convolutional neural network (CNN) based keyword spotting system using a small set of spoken isolated keywords. The…