Blind method for phone segmentation using Gaussian function locally

Phone segmentation is to divide a continuous speech signal into discrete, non-overlapping phone units. In this paper, a blind method for phone segmentation without using prior knowledge of speech content is proposed. A two-step algorithm for detecting phone boundaries is derived. The first step selects peaks of Euclidian curve as phone boundary candidates. The second step verifies these candidates using Gaussian function. The Gaussian function is computed locally. Therefore, it is suitable for speech feature at each local region of the utterance. Experiments show that our method is good for both short and long speech. Experiment 1 is conducted on a short speech corpus, the TIMIT. Our results are comparable to or more accurate than those of previous methods. Experiment 2 is conducted on a long speech corpus, the TCC300. Our results are more accurate than previous method. The relative improvement of F-value is 1.05%. This method is effective for long speech.