Cross-Correlation Based Automated Segmentation of Audio Samples.

This paper presents an audio file segmentation method in an attempt to mitigate the issue of variable durations of the same utterance by different individuals, e.g.: Speech-Language Pathologist (SLP) and dyslalic subjects. The Method section describes the manner of determination of the maximum cross-correlation value between the 2 audio files and the subsequent automated segmentation thereof in order to extract 2 valid pronunciation samples of the target consonant. The method is aimed at pre-processing audio files and supplying homogeneously-trimmed audio samples to a computerized SSD Screening system. The results obtained on a batch of 30 pronunciations are presented and briefly discussed in the third section while the last section is reserved for conclusions and perspectives.