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Mainly for the sake of solving the lack of keyword-specific data, we proposeone Keyword Spotting (KWS) system using Deep Neural Network (DNN) andConnectionist Temporal Classifier (CTC) on power-constrained small-footprintmobile devices, taking full advantage of general corpus from continuous speechrecognition which is of great amount. DNN is to directly predict the posteriorof phoneme units of any personally customized key-phrase, and CTC to produce aconfidence score of the given phoneme sequence as responsive decision-makingmechanism. The CTC-KWS has competitive performance in comparison with purelyDNN based keyword specific KWS, but not increasing any computationalcomplexity.

Small-footprint Keyword Spotting Using Deep Neural Network and Connectionist Temporal Classifier