  Mainly for the sake of solving the lack of keyword-specific data, we propose
one Keyword Spotting (KWS) system using Deep Neural Network (DNN) and
Connectionist Temporal Classifier (CTC) on power-constrained small-footprint
mobile devices, taking full advantage of general corpus from continuous speech
recognition which is of great amount. DNN is to directly predict the posterior
of phoneme units of any personally customized key-phrase, and CTC to produce a
confidence score of the given phoneme sequence as responsive decision-making
mechanism. The CTC-KWS has competitive performance in comparison with purely
DNN based keyword specific KWS, but not increasing any computational
complexity.
