Accurate speech segmentation by mimicking human auditory processing

This paper addresses the problem of locating phone boundaries without prior knowledge of the text of an utterance. A biomimetic model of human auditory processing is used to calculate the neural features of frequency synchrony and average signal level. Frequency synchrony and average signal level are used as input to a two-layered support vector machine (SVM)-based system to detect phone boundaries. Phone boundaries are detected with 87.0% precision and 84.8% recall when the automatic segmentation system has no prior knowledge of the phone sequence in the utterance.