Speech Recognition Using Recurrent Neural Network
Author(s):
Amitkumar O. Panchal
Keywords:
Speech Recognition, Recurrent Neural Network, MFCC, Feature Extraction, Principal Component Analysis
Abstract
The study on Speech Recognition (SR) and understanding has been done for many year. Speech is the vocalized form of human communication. Each spoken word is created out of the phonetic combination of a limited set of vowel and consonant speech sound units. SR is the ability of a machine or program to identify words and phrases in spoken language and convert them to a machine readable format. Today, however it uses continuous dictation, It is also become smarter with its own set of grammar rules to make out the meaning of what is being said. In this paper, we have a proposed alphabetical words of CORPUS database using MFCC (Mel Frequency Cepstral Coefficient) and Recurrent Neural Network method for a Speech Recogntion (SR).
Article Details
Unique Paper ID: 142636

Publication Volume & Issue: Volume 2, Issue 5

Page(s): 30 - 33
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