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Volumn , Issue , 2010, Pages 5290-5293

Integrating recognition and retrieval with user feedback: A new framework for spoken term detection

Author keywords

Discriminative training; Spoken term detection

Indexed keywords

ACOUSTICS MODEL; DISCRIMINATIVE TRAINING; LATTICE-BASED; MINIMUM CLASSIFICATION ERROR; MODELING PARAMETERS; PERFORMANCE; POSTERIOR PROBABILITY; RETRIEVAL TECHNIQUES; SPOKEN TERM DETECTION; USER FEEDBACK;

EID: 78049408076     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICASSP.2010.5494967     Document Type: Conference Paper
Times cited : (7)

References (14)
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  • 3
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  • 4
    • 51449096916 scopus 로고    scopus 로고
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  • 7
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    • H. Nanjo and T. Kawahara, "A new ASR evaluation measure and minimum bayes-risk decoding for open-domain speech understanding," in ICASSP, 2005.
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  • 8
    • 51449115420 scopus 로고    scopus 로고
    • Minimum bayes-risk decoding with presumed word significance for speech based information retrieval
    • T. Shichiri, H. Nanjo, and T. Yoshimi, "Minimum bayes-risk decoding with presumed word significance for speech based information retrieval," in ICASSP, 2008.
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  • 9
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  • 12
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  • 13
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    • Unsupervised lattice-based acoustic model adaptation for speaker-dependent conversational telephone speech transcription
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.