메뉴 건너뛰기




Volumn 3, Issue , 2012, Pages 2609-2612

Complementary Phone Error training

Author keywords

Acoustic model training; Complementary models; Discriminant training; Speech recognition; System combination

Indexed keywords

ACOUSTIC DATA; ACOUSTIC MODEL; ACOUSTIC MODEL TRAININGS; COMPLEMENTARY MODEL; LARGE VOCABULARY CONTINUOUS SPEECH RECOGNITION; MINIMUM PHONE ERROR; SYSTEM COMBINATION; WORD ERROR RATE;

EID: 84878590630     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (4)

References (11)
  • 2
    • 33646818291 scopus 로고    scopus 로고
    • Constructing ensembles of ASR systems using randomized decision trees
    • O. Siohan, O., B. Ramabhadran, & B. Kingsbury "Constructing Ensembles of ASR systems using Randomized Decision Trees", Proc. ICASSP, 2005.
    • (2005) Proc. ICASSP
    • Siohan, O.O.1    Ramabhadran, B.2    Kingsbury, B.3
  • 3
    • 79959833868 scopus 로고    scopus 로고
    • Building multiple complementary systems using directed decision trees
    • C. Breslin, & M.J.F. Gales "Building Multiple Complementary Systems using Directed Decision Trees", Proc. Interspeech, 2007.
    • (2007) Proc. Interspeech
    • Breslin, C.1    Gales, M.J.F.2
  • 4
    • 85009126846 scopus 로고    scopus 로고
    • A frame level boosting training scheme for acoustic modeling
    • R. Zhang & A.I. Rudnicky "A frame level boosting training scheme for acoustic modeling", Proc. ICSLP, 2004.
    • (2004) Proc. ICSLP
    • Zhang, R.1    Rudnicky, A.I.2
  • 5
    • 78049386242 scopus 로고    scopus 로고
    • Towards robust learning of gaussian mixture state emission densities for hidden Markov models
    • H. Tang, M. Hasegawa-Johnson & T.S. Huang "Towards Robust Learning of Gaussian Mixture State Emission Densities for Hidden Markov Models", Proc. ICASSP, 2010.
    • (2010) Proc. ICASSP
    • Tang, H.1    Hasegawa-Johnson, M.2    Huang, T.S.3
  • 6
    • 79959858643 scopus 로고    scopus 로고
    • Boosted mixture learning of gaussian mixture HMMs for speech recognition
    • J. Du, Y. Hu & H. Jiang "Boosted Mixture Learning of Gaussian Mixture HMMs for Speech Recognition", Proc. Interspeech, 2010.
    • (2010) Proc. Interspeech
    • Du, J.1    Hu, Y.2    Jiang, H.3
  • 8
    • 80055092534 scopus 로고    scopus 로고
    • Boosting systems for large vocabulary continuous speech recognition
    • G. Saon & H. Soltau "Boosting systems for large vocabulary continuous speech recognition", Speech Communication, 54:212-218, 2012.
    • (2012) Speech Communication , vol.54 , pp. 212-218
    • Saon, G.1    Soltau, H.2
  • 9
    • 0036296863 scopus 로고    scopus 로고
    • Minimum phone error and I-smoothing for improved discriminative training
    • D.Povey & P.C. Woodland "Minimum Phone Error and I-Smoothing for Improved Discriminative Training", Proc. ICASSP, 2002.
    • (2002) Proc. ICASSP
    • Povey, D.1    Woodland, P.C.2
  • 10
  • 11
    • 0001860529 scopus 로고    scopus 로고
    • A post-processing system to yield reduced word error rates: Recogniser output voting error reduction (ROVER)
    • J.G. Fiscus "A Post-Processing System to Yield Reduced Word Error Rates: Recogniser Output Voting Error Reduction (ROVER)", Proc. ASRU, 1997.
    • (1997) Proc. ASRU
    • Fiscus, J.G.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.