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. In this paper, we put these scientific motivations to the test by formulating a point process-based computational framework for the task of spotting keywords in continuous speech. We find that even with a noisy and extremely sparse phonetic landmark-based point process representation, keywords can be spotted with
This paper proposes a novel system for robust keyword detection in continuous speech. Our decoder is composed of a bidirectional Long Short-Term Memory recurrent neural network using a Connectionist Temporal Classification (CTC) output layer, and a Dynamic Bayesian Network (DBN). The CTC network exploits bidirectional
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