Automatic Disordered Syllables Repetition Recognition in Continuous Speech Using CWT and Correlation

Automatic disorder recognition in speech can be very helpful for the therapist while monitoring therapy progress of the patients with disordered speech. In this article the syllables repetition are described. The signal was analyzed using Continuous Wavelet Transform with bark scales, the result was divided into vectors (using windowing) and then a correlation algorithm was used on this data. Quite large search analysis was performed during which, recognition above 80% was achieved. All the analysis was performed and the results were obtained using the authors program - WaveBlaster. It is very important that the recognition ratio above 80% was obtained by a fully automatic algorithm (without a teacher) from the continuous speech. The presented problem is part of our research aimed at creating an automatic disorders recognition system.