Abstract

According to the visible characteristics of speech, a new speech recognition system design was proposed. It based on multiple neural networks. Firstly, Pulse Coupled Neural Network(PCNN) was input into the spectrogram for producing the corresponding time series icon as the feature parameters of speech. And then, the feature parameters was input into the Probabilistic Neural Networks(PNN) for training PNN to realizing speech recognition. Finally, the Probabilistic Neural Networks(PNN) was used of processing these feature parameters for realizing speech recognition. This way could solve the problem of template matching weak generalization of PCNN. As the simulation results shown, the higher speech recognition rate could be gotten by this way.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.