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  Text Independent Speaker Recognition and Speaker Independent Speech Recognition Using Iterative Clustering Approach
 
 
Titel: Text Independent Speaker Recognition and Speaker Independent Speech Recognition Using Iterative Clustering Approach
Auteur: A.Revathi
R.Ganapathy
Y.Venkataramani
Verschenen in: International journal of computer science and information technology
Paginering: Jaargang 1 (2009) nr. 2 pagina's 30-42
Jaar: 2009
Inhoud: This paper presents the effectiveness of perceptual features and iterative clustering approach forperforming both speech and speaker recognition. Procedure used for formation of training speech is differentfor developing training models for speaker independent speech and text independent speaker recognition. So,this work mainly emphasizes the utilization of clustering models developed for the training data to obtainbetter accuracy as 91%, 91% and 99.5% for mel frequency perceptual linear predictive cepstrum with respectto three categories such as speaker identification, isolated digit recognition and continuous speechrecognition. This feature also produces 9% as low equal error rate which is used as a performance measurefor speaker verification. The work is experimentally evaluated on the set of isolated digits and continuousspeeches from TI digits_1 and TI digits_2 database for speech recognition and on speeches of 50 speakersrandomly chosen from TIMIT database for speaker recognition. The noteworthy feature of speakerrecognition algorithm is to evaluate the testing procedure on identical messages of all the 50 speakers,theoretical validation of results using F-ratio and validation of results by statistical analysis using2 cdistribution.
Uitgever: Academy & Industry Research Collaboration Center (AIRCC) (provided by DOAJ)
Bronbestand: Elektronische Wetenschappelijke Tijdschriften
 
 

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