Cooperative static and dynamic neural networks for phoneme recognition

This paper investigates the use of static and dynamic neural networks in phoneme recognition. Besides this, the paper also proposes a cooperative static and dynamic neural networks model. The cooperative model integrates a decision system for phoneme recognition. Mel cepstrum coding has been applied to represent speech signal in frames. Features from the selected frames are used to train neural networks based models. The comparative study show that the proposed cooperative model provides more accurate recognition rates both in auto-coherence test and generalization test.