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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 aim is to allow rapid deployment of a keyword spotting system in a new language to support urgent United Nations (UN) relief programmes in parts of Africa where languages are extremely under-resourced and the development of annotated speech resources is infeasible. First, we use 1920 recorded keywords (40 keyworddoi:10.21437/interspeech.2018-1580 dblp:conf/interspeech/MenonKQN18 fatcat:tks2v3atb5fj7iznm3bxzzdrr4