On the Use of Recurrent Neural Networks for Grammar Learning and Word Spotting
In this work we try to infer from the speech all the possible sequences of allophones and their distribution over time by using a recursive network architecture, in which its recurrent connections learn phoneme sequence relationships. We describe some experiments in the context of Keyword Spotting.
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