Speaker phone mode classification using Gaussian mixture models
Hamid Eghbal-zadeh, Fariborz Sobhanmanesh, Hossein Sameti, Bagher BabaAli · Signal Processing: Algorithms, Architectures, Arrangements, and Applications · 2011
This study focuses on the mode classification of phones speaker modes using GMM1. In this regard, speech data in both enabled and disabled speaker modes of cell phones and telephones were collected, processed and classified into two different categories. The different mixture numbers (1 to 4) of GMM and wave files sizes of 10, 20, 40 and 80 kb were tested in order to obtain an optimal condition for classification. The GMM method attained 87.99% correct classification rate on test data. This classification is important for speech enabled IVR2 systems [1], dialog systems and many systems in speech processing in the sense that it could help to load an optimum model for increasing system accuracy.