Comparative Analysis of Speech Recognition Based on Artificial Neural Network
Abhinav Bhatnagar, Sapna Sinha
speech recognition, HMM, genetic algorithms, MFCC, FBCC, P.S.O, Back propagation algorithm Neural networks, speech recognition.
People feels very comfortable with the speech so they want to interact with computers via their voice rather than hardware interfaces devices like keyboards and pointing devices. Speech is the easy and common medium to communicate with real system but unwanted voice signal comes during communication. In this paper presents comparative analyses of the different methods used for better recognition. There are three types of categories of speech enhancement algorithms filtering based noise reduction, beam forming and active noise cancellation (A.N.C) techniques. Artificial Neural Network(A.N.N) is speech recognition platform which has better speed of recognition and Recent work shows improved performance results when G.A is applied on speech signals recorded when noise comes and interrupted. The work here applies developmental reckoning in type of hereditary calculation to choose the highlights that are in charge of segregating the distinctive words. This will improve recognition and reduces the unwanted noise
Article Details
Unique Paper ID: 142325

Publication Volume & Issue: Volume 2, Issue 1

Page(s): 35 - 39
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Last Date 25 December 2018

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