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Volumn , Issue , 2011, Pages 5452-5455

Using clustering comparison measures for speaker recognition

Author keywords

normalised information distance; normalised mutual information; speaker recognition; UBM training

Indexed keywords

ACOUSTIC FEATURES; COMPARISON MEASURES; DATA SELECTION; DIFFERENT ORIGINS; INFORMATION DISTANCE; MODULATION INFORMATION; MUTUAL INFORMATIONS; RECOGNITION ACCURACY; RELATIVE REDUCTION; SPEAKER RECOGNITION; SPEAKER RECOGNITION SYSTEM; TRAINING DATA SETS; UBM TRAINING;

EID: 80051635968     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICASSP.2011.5947592     Document Type: Conference Paper
Times cited : (4)

References (13)
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  • 5
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    • Training Universal Background Models for Speaker Recognition
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    • (2010) IBM Research Report
    • Omar, M.K.1    Pelecanos, J.2
  • 7
    • 70350125882 scopus 로고    scopus 로고
    • An overview of text-independent speaker recognition: From features to supervectors
    • T. Kinnunen and H. Li, "An overview of text-independent speaker recognition: from features to supervectors," Speech Communication, vol. 52, pp. 12-40, 2010.
    • (2010) Speech Communication , vol.52 , pp. 12-40
    • Kinnunen, T.1    Li, H.2
  • 8
    • 0041965980 scopus 로고    scopus 로고
    • Cluster ensembles - A knowledge reuse framework for combining multiple partitions
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    • Strehl, A.1    Ghosh, J.2
  • 9
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    • Information Theoretic Measures for Clusterings Comparison: Variants, Properties, Normalization and Correction for Chance
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    • Vinh, N.X.1    Epps, J.2    Bailey, J.3    Houle, M.4
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  • 13
    • 78049375621 scopus 로고    scopus 로고
    • A novel feature sub-sampling method for efficient universal background model training in speaker verification
    • T. Hasan, Y. Lei, A. Chandrasekaran, and J. H. L. Hansen, "A novel feature sub-sampling method for efficient universal background model training in speaker verification," in ICASSP, 2010, pp. 4494-4497.
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.