{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T10:14:19Z","timestamp":1777889659532,"version":"3.51.4"},"reference-count":31,"publisher":"SAGE Publications","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["KES"],"published-print":{"date-parts":[[2021,11,10]]},"abstract":"<jats:p>Speaker Identification denotes the speech samples of known speaker and it identifies the best matches of the input model. The SGMFC method is the combination of Sub Gaussian Mixture Model (SGMM) with the Mel-frequency Cepstral Coefficients (MFCC) for feature extraction. The SGMFC method minimizes the error rate, memory footprint and also computational throughput measure needs of a medium-vocabulary speaker identification system, supposed for preparation on a transportable or otherwise. Fuzzy C-means and k-means clustering are used in the SGMM method to attain the improved efficiency and their outcomes with parameters such as precision, sensitivity and specificity are compared.<\/jats:p>","DOI":"10.3233\/kes-210073","type":"journal-article","created":{"date-parts":[[2021,11,16]],"date-time":"2021-11-16T12:26:36Z","timestamp":1637065596000},"page":"309-314","source":"Crossref","is-referenced-by-count":2,"title":["Speaker identification analysis for SGMM with k-means and fuzzy C-means clustering using SVM statistical technique"],"prefix":"10.1177","volume":"25","author":[{"given":"K.","family":"Manikandan","sequence":"first","affiliation":[{"name":"Department of Computer Science, PSG College of Arts and Science, Coimbatore, India"}]},{"given":"E.","family":"Chandra","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Bharathiar University, Coimbatore, India"}]}],"member":"179","reference":[{"issue":"1","key":"10.3233\/KES-210073_ref1","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1109\/89.365379","article-title":"Robust text-independent speaker identification using Gaussian mixture speaker models","volume":"3","author":"Reynolds","year":"1995","journal-title":"IEEE Trans Speech Audio Process"},{"issue":"4","key":"10.3233\/KES-210073_ref2","doi-asserted-by":"crossref","first-page":"561","DOI":"10.1109\/PROC.1975.9792","article-title":"Linear prediction: A tutorial review","volume":"63","author":"Makhoul","year":"1975","journal-title":"Proc IEEE"},{"issue":"3","key":"10.3233\/KES-210073_ref3","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1109\/97.372913","article-title":"Large population speaker identification using clean and telephone speech","volume":"2","author":"Reynolds","year":"1995","journal-title":"IEEE Signal Process Lett"},{"issue":"1\u20132","key":"10.3233\/KES-210073_ref4","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1016\/0167-6393(95)00009-D","article-title":"Speaker identification and verification using Gaussian mixture speaker models","volume":"17","author":"Reynolds","year":"1995","journal-title":"Speech Commun"},{"issue":"11","key":"10.3233\/KES-210073_ref5","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1109\/97.728467","article-title":"An efficient scoring algorithm for gaussian mixture model based speaker identification","volume":"5","author":"Pellom","year":"1998","journal-title":"IEEE Signal Process Lett"},{"issue":"6","key":"10.3233\/KES-210073_ref6","doi-asserted-by":"crossref","first-page":"778","DOI":"10.1109\/3477.809032","article-title":"A survey of fuzzy clustering algorithms for pattern identification","volume":"29","author":"Baraldi","year":"1999","journal-title":"IEEE Trans Syst, Man, Cybern, B: Cybern"},{"issue":"1\u20133","key":"10.3233\/KES-210073_ref7","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1006\/dspr.1999.0361","article-title":"Speaker verification using adapted Gaussian mixture models","volume":"10","author":"Reynolds","year":"2000","journal-title":"Digital Signal Process"},{"key":"10.3233\/KES-210073_ref8","unstructured":"C. Wang, Prosodic modeling for improved speech identification and understanding, Ph.D. dissertation, Mass Inst of Technol, Cambridge, MA, 2001."},{"key":"10.3233\/KES-210073_ref9","doi-asserted-by":"crossref","unstructured":"H. Ezzaidi, J. Rouat and D. O\u2019Shaughnessy, Towards combining pitch and mfcc for speaker identification systems, in: Proc 7th Eur Conf Speech Commun Technol, 2001.","DOI":"10.21437\/Eurospeech.2001-661"},{"key":"10.3233\/KES-210073_ref10","doi-asserted-by":"crossref","first-page":"461","DOI":"10.1109\/ICASSP.2001.940867","article-title":"Very large population text-independent speaker identification using transformation enhanced multi-grained models","volume":"1","author":"Chaudhari","year":"2001","journal-title":"Proc IEEE Int Conf Acoust, Speech, Signal Process (ICASSP\u201901)"},{"key":"10.3233\/KES-210073_ref11","doi-asserted-by":"crossref","first-page":"1917","DOI":"10.1121\/1.1458024","article-title":"Yin, a fundamental frequency estimator for speech and music","volume":"111","author":"De\u00a0Cheveign\u00e9","year":"2002","journal-title":"J Acoust Soc Amer"},{"key":"10.3233\/KES-210073_ref12","doi-asserted-by":"crossref","first-page":"365","DOI":"10.1109\/MMSP.2007.4412892","article-title":"Combining vocal source and MFCC features for enhanced speaker identification performance using GMMS","author":"Hosseinzadeh","year":"2007","journal-title":"IEEE 9th Workshop Multimedia Signal Process MMSP\u201907"},{"issue":"6","key":"10.3233\/KES-210073_ref13","doi-asserted-by":"crossref","first-page":"1097","DOI":"10.1109\/TASL.2008.2001109","article-title":"Speaker identification using instantaneous frequencies","volume":"16","author":"Grimaldi","year":"2008","journal-title":"IEEE Trans Audio, Speech, Lang Process"},{"issue":"4","key":"10.3233\/KES-210073_ref14","doi-asserted-by":"crossref","first-page":"848","DOI":"10.1109\/TASL.2008.2010882","article-title":"Speaker model clustering for efficient speaker identification in large population applications","volume":"17","author":"Apsingekar","year":"2009","journal-title":"IEEE Trans Audio, Speech, Language Process"},{"key":"10.3233\/KES-210073_ref15","first-page":"1","article-title":"Fast approach to speaker identification for large population using mllr and sufficient statistics","author":"Sarkar","year":"2010","journal-title":"Proc National Conf Commun (NCC)"},{"issue":"2","key":"10.3233\/KES-210073_ref16","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1109\/MCAS.2011.941079","article-title":"An overview of speaker identification: Accuracy and robustness issues","volume":"11","author":"Togneri","year":"2011","journal-title":"IEEE Circuits Syst Mag"},{"issue":"4","key":"10.3233\/KES-210073_ref17","doi-asserted-by":"crossref","first-page":"788","DOI":"10.1109\/TASL.2010.2064307","article-title":"Front-end factor analysis for speaker verification","volume":"19","author":"Dehak","year":"2011","journal-title":"IEEE Trans Audio, Speech, Lang Process"},{"key":"10.3233\/KES-210073_ref18","doi-asserted-by":"crossref","unstructured":"Y. Hu, D. Wu and A. Nucci, Pitch-based gender identification with two-stage classification, Security Commun Netw (2011).","DOI":"10.1002\/sec.308"},{"issue":"1","key":"10.3233\/KES-210073_ref19","doi-asserted-by":"crossref","first-page":"196","DOI":"10.1109\/TASL.2010.2045800","article-title":"Robust speaker identification using denoised vocal source and vocal tract features","volume":"19","author":"Wang","year":"2011","journal-title":"IEEE Trans Audio, Speech, Lang Process"},{"key":"10.3233\/KES-210073_ref20","doi-asserted-by":"crossref","first-page":"612","DOI":"10.1007\/978-3-642-21257-4_76","article-title":"On the use of dot scoring for speaker diarization","author":"Diez","year":"2011","journal-title":"Pattern Recogn and Image Anal"},{"issue":"4","key":"10.3233\/KES-210073_ref21","doi-asserted-by":"crossref","first-page":"1085","DOI":"10.1109\/TASL.2011.2172422","article-title":"Speaker characterization and identification-speaker identification and verification by combining mfcc and phase information","volume":"20","author":"Nakagawa","year":"2012","journal-title":"IEEE Trans Audio, Speech, Lang Process"},{"key":"10.3233\/KES-210073_ref22","doi-asserted-by":"crossref","unstructured":"Y. Hu, D. Wu and A. Nucci, Fuzzy-clustering-based decision tree approach for large population speaker identification, IEEE Transactions On Audio, Speech, and Language Processing 21(4) (2013).","DOI":"10.1109\/TASL.2012.2234113"},{"key":"10.3233\/KES-210073_ref23","unstructured":"E. Chandra, K. Manikandan and M. Sivasankar, A proportional study on feature extraction method in automatic speech identification system, Ijireeice 2(1) (2014)."},{"key":"10.3233\/KES-210073_ref24","first-page":"319","article-title":"A hybrid GMM-SVM speaker identification system","volume":"1","author":"Mashao","year":"2004","journal-title":"AFRICON, IEEE"},{"key":"10.3233\/KES-210073_ref25","doi-asserted-by":"crossref","unstructured":"S. Madikeri, P. Motlicek and H. Bourand, Combining SGMM speaker vectors and KL-HMM approach for Speaker Diarization, ICASSP, IEEE, (2015).","DOI":"10.1109\/ICASSP.2015.7178889"},{"issue":"4","key":"10.3233\/KES-210073_ref26","doi-asserted-by":"crossref","first-page":"848","DOI":"10.1109\/TASL.2008.2010882","article-title":"Speaker model clustering for efficient speaker identification in large population applications","volume":"17","author":"Leon","year":"2009","journal-title":"IEEE Transactions on Audio, Speech, and Language Processing"},{"issue":"2","key":"10.3233\/KES-210073_ref27","first-page":"404","article-title":"The subspace gaussian mixturemodel\u00a0\u2013 a structured model for speech recognition","volume":"25","author":"Povey","year":"2011","journal-title":"ComputerSpeech and Language"},{"key":"10.3233\/KES-210073_ref28","doi-asserted-by":"crossref","unstructured":"V.K. Verma and N. Khanna, Indian language identification using k-means clustering and support vector machine (SVM), Engineering and Systems (SCES), IEEE, (2013).","DOI":"10.1109\/SCES.2013.6547533"},{"key":"10.3233\/KES-210073_ref29","doi-asserted-by":"crossref","unstructured":"S. Ghosh and S. Kumar\u00a0Dubery, Comparative analysis of k-means and fuzzy C-means algorithm, IJACSA 4(4) (2013).","DOI":"10.14569\/IJACSA.2013.040406"},{"key":"10.3233\/KES-210073_ref30","unstructured":"S. Sahu and N. Dharmale, Controlling the application via speech processing through mel frequency cepstral coefficients and back propagation neural method 3(2) (2016)."},{"key":"10.3233\/KES-210073_ref31","first-page":"592","article-title":"Comparative mixture, fuzzy C-means algorithms for brain tumor segmentation","volume":"137","author":"Baid","year":"2016","journal-title":"ICCASP"}],"container-title":["International Journal of Knowledge-based and Intelligent Engineering Systems"],"original-title":[],"link":[{"URL":"https:\/\/content.iospress.com\/download?id=10.3233\/KES-210073","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T05:13:50Z","timestamp":1777612430000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/full\/10.3233\/KES-210073"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,11,10]]},"references-count":31,"journal-issue":{"issue":"3"},"URL":"https:\/\/doi.org\/10.3233\/kes-210073","relation":{},"ISSN":["1327-2314","1875-8827"],"issn-type":[{"value":"1327-2314","type":"print"},{"value":"1875-8827","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,11,10]]}}}