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Volumn 4274 LNAI, Issue , 2006, Pages 399-409

A minimum boundary error framework for automatic phonetic segmentation

Author keywords

Automatic phonetic segmentation; Discriminative training; Minimum Bayes risk; Minimum boundary error

Indexed keywords

AUTOMATIC SPEECH RECOGNITION; BOUNDARY ERRORS; CONTINUOUS SPEECH CORPUS; DECODING ALGORITHM; DISCRIMINATIVE TRAINING; MINIMUM BAYES RISK; MINIMUM PHONE ERROR; PHONETIC ALIGNMENT; PHONETIC SEGMENTATION;

EID: 77249165009     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11939993_43     Document Type: Conference Paper
Times cited : (5)

References (12)
  • 1
    • 0004565879 scopus 로고    scopus 로고
    • High-quality speech synthesis for phonetic speech segmentation
    • Malfrere, F., Dutiot, T.: High-quality speech synthesis for phonetic speech segmentation. Proc, Fifth Eurospeech (1997) 2631-2634
    • (1997) Proc, Fifth Eurospeech , pp. 2631-2634
    • Malfrere, F.1    Dutiot, T.2
  • 3
    • 0027646354 scopus 로고
    • Automatic segmentation and labeling of speech based on Hidden Markov Models
    • Brugnara, F., Falavigna, D., Omologo, M.: Automatic segmentation and labeling of speech based on Hidden Markov Models. Speech Communication, Vol.12, Issue, 4 (1993) 357-370
    • (1993) Speech Communication , vol.12 , Issue.4 , pp. 357-370
    • Brugnara, F.1    Falavigna, D.2    Omologo, M.3
  • 5
    • 44949200429 scopus 로고    scopus 로고
    • Minimum boundary error training for automatic phonetic segmentation
    • Kuo, J.-W., Wang, H.-M.: Minimum Boundary Error Training for Automatic Phonetic Segmentation. Proc. Interspeech-ICSLP (2006)
    • (2006) Proc. Interspeech-ICSLP
    • Kuo, J.-W.1    Wang, H.-M.2
  • 6
    • 0025627406 scopus 로고
    • The N-best algorithms: An efficient and exact procedure for finding the N most likely sentence hypotheses
    • Schwartz, R., Chow, Y.-L.: The N-best algorithms: an efficient and exact procedure for finding the N most likely sentence hypotheses. Proc. ICASSP, Vol.1(1990) 81-84
    • (1990) Proc. ICASSP , vol.1 , pp. 81-84
    • Schwartz, R.1    Chow, Y.-L.2
  • 7
    • 0030719155 scopus 로고    scopus 로고
    • A word graph algorithm for large vocabulary continuous speech recognition
    • Ortmanns,S.,Ney,H.,Aubert,X.: Awordgraphalgorithmforlargevocabularycontinuousspeechrecognition. ComputerSpeechandLanguage,Vol.11(1997)43-72(Pubitemid127375893)
    • (1997) Computer Speech and Language , vol.11 , Issue.1 , pp. 43-72
    • Ortmanns, S.1    Ney, H.2    Aubert, X.3
  • 8
    • 0025952278 scopus 로고
    • An inequality for rational functions with applications to some statistical estimation problems
    • Gopalakrishnan, P., Kanevsky, D., Nadas, A., Nahamoo, D.: An inequality for rational functions with applications to some statistical estimation problems, IEEE Trans. Information Theory, Vol.37 (1991) 107-113
    • (1991) IEEE Trans. Information Theory , vol.37 , pp. 107-113
    • Gopalakrishnan, P.1    Kanevsky, D.2    Nadas, A.3    Nahamoo, D.4
  • 10
    • 0036296863 scopus 로고    scopus 로고
    • Minimum phone error and I-smoothing for improved discriminative training
    • Povey, D., Woodland, P. C.: Minimum phone error and I-smoothing for improved discriminative training, Proc. ICASSP, Vol.1 (2002) 105-108
    • (2002) Proc. ICASSP , vol.1 , pp. 105-108
    • Povey, D.1    Woodland, P.C.2
  • 11
    • 0002583871 scopus 로고
    • Speech database development: Design and analysis of the acoustic-phonetic corpus
    • Lamel, L., Kasel, R., Seneff, S.: Speech database development: design and analysis of the acoustic-phonetic corpus, Proc. DARPA Speech Recognition Workshop (1986) 100-109
    • (1986) Proc. DARPA Speech Recognition Workshop , pp. 100-109
    • Lamel, L.1    Kasel, R.2    Seneff, S.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.