Segment boundary estimation using recurrent neural networks

This paper describes a segment (e.g. phoneme) boundary estimation method based on recurrent neural networks (RNNs). The proposed method only requires acoustic observations to accurately estimate segment boundaries. Experimental results show that the proposed method can estimate segment boundaries signi cantly better than an HMM based method. Furthermore, we incorporate the RNN based segment boundary estimator into the HMM based and segment based recognition systems. As a result, the segment boundary estimates give useful information for reducing computational complexity and improving recognition performance.

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