Identification of epochs from speech signals is a prominent task in speech processing. In this paper, epoch extraction is attempted from phase spectrum of speech signals. The phase spectrum of speech is modelled as an allpass (AP) filter by minimizing entropy of energy in the associated error signal. The AP residual thus obtained contains prominent unambiguous peaks at epoch locations. These peaks in AP residual constitute a set of candidate epoch locations from which appropriate ones are identified using a dynamic programming algorithm. The proposed method is evaluated on a subset of CMU Arctic database and it is observed that it delivered better epoch extraction performance than the prominent speech events estimation method-DYPSA. In case of telephone channel speech, the proposed method significantly outperformed zero frequency resonator based method also.
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