COMPARISON OF EFFICIENCY FOR SPEECH RECOGNITION BETWEEN NEURAL NETWORK AND CORRELATION
Journal: International Journal of Application or Innovation in Engineering & Management (IJAIEM) (Vol.4, No. 5)Publication Date: 2015-06-20
Authors : Er. Pooja Mittal; A.P.Kapil sachdeva; A.P.Lovely Dhawan;
Page : 389-394
Keywords : KEYWORDS: Speech Production; framing of speech signals; cross correlation; auto correlation MFCC; feed forward neural network.;
Abstract
ABSTRACT In this paper an efficiency of the speech recognition system is compared between the correlation and neural network to recognize Hindi words in MATLAB. This paper takes a brief look at the basic building block of a speech recognition engine. It talks about implementation of different types of modules i.e. Sound Recorder, Framing, Correlation, Feature Extractor and Neural Network Training. In real life, this speech recognition technology might be used in voice calling, call center automation, in data entry, in medical documentation, etc.
Other Latest Articles
- Utilize Eye Tracking Technique to Control Devices for ALS Patients
- Vehicle Plate Extraction and Recognition using Hopfield Neural Network and Comparison with DWT, Correlation and NN Algorithms
- Studies On Influence Of Injection Pressure On Performance Parameters Of Diesel Engine With Medium Grade Insulated Combustion Chamber With Crude Jatropha Oil Operation
- Performance Evaluation and Heat transfer studies on Biomass Gasifier cook-stove
- IMPROVED NEGATIVE SELECTION BASED DECISION BASED MEDIAN FILTER FOR NOISE REMOVAL
Last modified: 2015-06-15 13:51:49