The application of polynomial discriminant function classifiers to isolated arabic speech recognition
Source of Publication
IEEE International Conference on Neural Networks - Conference Proceedings
In this paper, we apply polynomial discriminant function classifiers for isolated-word speaker-independent Arabic digit recognition. The performance of the polynomial classifier is evaluated for different implementations. We also provide a performance comparison between the polynomial classifier and Dynamic Time Warping (DTW). The polynomial classifier is found to outperform DTW in many aspects such as recognition rate, and computational and memory requirements.
Khasawneh, Mohammed; Assaleh, Khaled; Sweidan, Wesam; and Haddad, Monther, "The application of polynomial discriminant function classifiers to isolated arabic speech recognition" (2004). Scopus Indexed Articles. 2528.