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Volumn , Issue , 2013, Pages 1-5

Information retrieval-based dynamic time warping

Author keywords

Dynamic programming; Dynamic time warping; Information retrieval; Mediaeval; Zero resources

Indexed keywords

ALGORITHMS; DYNAMIC PROGRAMMING;

EID: 84906256597     PISSN: 2308457X     EISSN: 19909772     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (17)

References (22)
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  • 3
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    • Y. Zhang, K. Adl, and J. Glass, "Fast Spoken Query Detection using Lower-Bound Dynamic Time Warping on Graphical Processing Units, " in ICASSP, 2012, pp. 5173-5176.
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    • Zhang, Y.1    Adl, K.2    Glass, J.3
  • 4
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    • A piecewise aggregate approximation lower-bound estimate for posteriorgram-based dynamic time warping
    • Y. Zhang and J. Glass, "A Piecewise Aggregate Approximation Lower-Bound Estimate for Posteriorgram-based Dynamic Time Warping, " in Interspeech, 2011, pp. 1909-1912.
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    • Zhang, Y.1    Glass, J.2
  • 7
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    • Towards spoken term discovery at scale with zero resources
    • Makuhari, Japan
    • A. Jansen, K. Church, and H. Hermansky, "Towards Spoken Term Discovery at Scale with Zero Resources, " in Interspeech, Makuhari, Japan, 2010, pp. 1676-1679.
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    • Jansen, A.1    Church, K.2    Hermansky, H.3
  • 9
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    • Partial sequence matching using an unbounded dynamic time warping algorithm
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    • Anguera, X.1    Macrae, R.2    Oliver, N.3
  • 10
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    • Indexing raw acoustic features for scalable zero resource search
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  • 12
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    • Wang, A.L.-C.1    Street, K.H.2
  • 14
    • 84890443127 scopus 로고    scopus 로고
    • Speed improvements to information retrieval-based dynamic time warping using hierarchical k-means clustering
    • G. Mantena and X. Anguera, "Speed Improvements to Information Retrieval-Based Dynamic Time Warping using Hierarchical k-Means Clustering, " in ICASSP, 2013.
    • (2013) ICASSP
    • Mantena, G.1    Anguera, X.2
  • 15
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    • Dynamic time warping
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  • 17
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  • 18
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  • 20
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    • ASR corpus design for resource-scarce languages
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.