Skip navigation
Indian Literature Database on Communication Disorders

Indian Literature Database
on Communication Disorders

Smiley face


Home


Categories &
Resource Types


Author


Title


Year


Subject


Login/Register

Please use this identifier to cite or link to this item: http://localhost:8080//handle/123456789/1025
Full metadata record
DC FieldValueLanguage
dc.contributor.authorThakur, A S-
dc.contributor.authorSahayam, N-
dc.date.accessioned2020-09-01T08:56:34Z-
dc.date.available2020-09-01T08:56:34Z-
dc.date.issued2013-
dc.identifier.issn2250-2459-
dc.identifier.urihttp://203.129.241.91:8080//handle/123456789/1025-
dc.description.abstractDigital processing of speech signal and voice recognition algorithm is very important for fast and accurate automatic voice recognition technology. The voice is a signal of infinite information. A direct analysis and synthesizing the complex voice signal is due to too much information contained in the signal. Therefore the digital signal processes such as Feature Extraction and Feature Matching are introduced to represent the voice signal. This paper describes an approach of speech recognition by using the Mel-Scale Frequency Cepstral Coefficients (MFCC) extracted from speech signal of spoken words. Verification is carried out using a weighted Euclidean distance. For speech recognition we implement the MFCC approach using software platform MatlabR2010b.en_US
dc.language.isoenen_US
dc.subjectSpeech recognitionen_US
dc.titleSpeech Recognition using Euclidean Distanceen_US
dc.typeArticleen_US
dc.journalname.journalnameInternational Journal of Emerging Technology and Advanced Engineeringen_US
dc.volumeno.volumeno3en_US
dc.issueno.issueno3en_US
dc.pages.pages587-590en_US
Appears in Resource:Journal Articles

Files in This Item:
File Description SizeFormat 
Speech recognition using euclidean distance.pdf601.52 kBAdobe PDFView/Open
Show simple item record


Items in Database are protected by copyright, with all rights reserved, unless otherwise indicated.