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Volumn 11, Issue 2, 1999, Pages 541-563

Hidden neural networks

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; ARTIFICIAL NEURAL NETWORK; AUTOMATED PATTERN RECOGNITION; DATA BASE; HUMAN; PROBABILITY; SPEECH PERCEPTION; STATISTICAL MODEL;

EID: 0033556867     PISSN: 08997667     EISSN: None     Source Type: Journal    
DOI: 10.1162/089976699300016764     Document Type: Review
Times cited : (43)

References (46)
  • 2
    • 0022890536 scopus 로고
    • Maximum mutual information estimation of hidden Markov model parameters for speech recognition
    • Bahl, L. R., Brown, P. F., de Souza, P. V., & Mercer, R. L. (1986). Maximum mutual information estimation of hidden Markov model parameters for speech recognition. In Proceedings of ICASSP'86 (pp. 49-52).
    • (1986) Proceedings of ICASSP'86 , pp. 49-52
    • Bahl, L.R.1    Brown, P.F.2    De Souza, P.V.3    Mercer, R.L.4
  • 3
    • 0001588636 scopus 로고
    • Smooth on-line learning algorithms for hidden Markov models
    • Baldi, P., & Chauvin, Y. (1994). Smooth on-line learning algorithms for hidden Markov models. Neural Computation, 6(2), 307-318.
    • (1994) Neural Computation , vol.6 , Issue.2 , pp. 307-318
    • Baldi, P.1    Chauvin, Y.2
  • 4
    • 0030266582 scopus 로고    scopus 로고
    • Hybrid modeling, HMM/NN architectures, and protein applications
    • Baldi, P., & Chauvin, Y. (1996). Hybrid modeling, HMM/NN architectures, and protein applications. Neural Computation, 8, 1541-1565.
    • (1996) Neural Computation , vol.8 , pp. 1541-1565
    • Baldi, P.1    Chauvin, Y.2
  • 5
    • 33646941615 scopus 로고    scopus 로고
    • An EM algorithm for asynchronous input/output hidden Markov models
    • Bengio, S., & Bengio, Y. (1996). An EM algorithm for asynchronous input/output hidden Markov models. In Proceedings of the ICONIP'96.
    • (1996) Proceedings of the ICONIP'96
    • Bengio, S.1    Bengio, Y.2
  • 8
    • 0029411630 scopus 로고
    • Lerec: A NN/HMM hybrid for on-line handwritting recognition
    • Bengio, Y., LeCun, Y., Nohl, C., & Burges, C. (1995). Lerec: A NN/HMM hybrid for on-line handwritting recognition. Neural Computation, 7(5).
    • (1995) Neural Computation , vol.7 , Issue.5
    • Bengio, Y.1    LeCun, Y.2    Nohl, C.3    Burges, C.4
  • 11
    • 0025385598 scopus 로고
    • Alphanets: A recurrent "neural" network architecture with a hidden Markov model interpretation
    • Bridle, J. S. (1990). Alphanets: A recurrent "neural" network architecture with a hidden Markov model interpretation. Speech Communication, 9, 83-92.
    • (1990) Speech Communication , vol.9 , pp. 83-92
    • Bridle, J.S.1
  • 12
    • 0002629270 scopus 로고
    • Maximum likelihood from incomplete data via the EM algorithm
    • Dempster, A. P., Laird, N. M., & Rubin, D. B. (1977). Maximum likelihood from incomplete data via the EM algorithm. Royal Statistical Society B, 39, 1-38.
    • (1977) Royal Statistical Society B , vol.39 , pp. 1-38
    • Dempster, A.P.1    Laird, N.M.2    Rubin, D.B.3
  • 16
    • 0025952278 scopus 로고
    • An inequality for rational functions with applications to some statistical estimation problems
    • Gopalakrishnan, P. S., Kanevsky, D., Nádas, A., & Nahamoo, D. (1991). An inequality for rational functions with applications to some statistical estimation problems. IEEE Transactions on Information Theory, 37(1), 107-113.
    • (1991) IEEE Transactions on Information Theory , vol.37 , Issue.1 , pp. 107-113
    • Gopalakrishnan, P.S.1    Kanevsky, D.2    Nádas, A.3    Nahamoo, D.4
  • 17
    • 0031122868 scopus 로고    scopus 로고
    • A comparison of new and old algorithms for a mixture estimation problem
    • Helmbold, D. P., Schapire, R. E., Singer, Y., & Warmuth, M. K. (1997). A comparison of new and old algorithms for a mixture estimation problem. Machine Learning, 27(1), 97-119.
    • (1997) Machine Learning , vol.27 , Issue.1 , pp. 97-119
    • Helmbold, D.P.1    Schapire, R.E.2    Singer, Y.3    Warmuth, M.K.4
  • 20
    • 0005802482 scopus 로고
    • Global optimisation of HMM input transformations
    • Johansen, F. T. (1994). Global optimisation of HMM input transformations. In Proceedings of ICSLP'94 (Vol. 1, pp. 239-242).
    • (1994) Proceedings of ICSLP'94 , vol.1 , pp. 239-242
    • Johansen, F.T.1
  • 21
    • 0005880122 scopus 로고
    • Non-linear input transformations for discriminative HMMs
    • Johansen, F. T., & Johnsen, M. H. (1994). Non-linear input transformations for discriminative HMMs. In Proceedings of ICASSP'94 (Vol. 1, pp. 225-228).
    • (1994) Proceedings of ICASSP'94 , vol.1 , pp. 225-228
    • Johansen, F.T.1    Johnsen, M.H.2
  • 22
    • 0026206264 scopus 로고
    • Hidden Markov models for speech recognition
    • Juang, B. H., & Rabiner, L. R. (1991). Hidden Markov models for speech recognition. Technometrics, 33(3), 251-272.
    • (1991) Technometrics , vol.33 , Issue.3 , pp. 251-272
    • Juang, B.H.1    Rabiner, L.R.2
  • 23
    • 0008815681 scopus 로고    scopus 로고
    • Exponentiated gradient versus gradient descent for linear predictors
    • Kivinen, J., & Warmuth, M. K. (1997). Exponentiated gradient versus gradient descent for linear predictors. Information and Computation, 132(1), 1-63.
    • (1997) Information and Computation , vol.132 , Issue.1 , pp. 1-63
    • Kivinen, J.1    Warmuth, M.K.2
  • 24
    • 0024124595 scopus 로고
    • Statistical pattern recognition with neural networks: Benchmarking studies
    • Kohonen, T., Barna, G., & Chrisley, R. (1988). Statistical pattern recognition with neural networks: Benchmarking studies. In Proceedings of ICNN'88 (Vol. 1, pp. 61-68).
    • (1988) Proceedings of ICNN'88 , vol.1 , pp. 61-68
    • Kohonen, T.1    Barna, G.2    Chrisley, R.3
  • 25
    • 84910103509 scopus 로고    scopus 로고
    • REMAP: Recursive estimation and maximization of a posteriori probabilities Application to transition-based connectionist speech recognition
    • D. S. Touretzky, M. C. Mozer, & M. E. Hasselmo (Eds.), Cambridge, MA: MIT Press
    • Konig, Y., Bourlard, H., & Morgan, N. (1996). REMAP: Recursive estimation and maximization of a posteriori probabilities - Application to transition-based connectionist speech recognition. In D. S. Touretzky, M. C. Mozer, & M. E. Hasselmo (Eds.), Advances in neural information processing systems, 8 (pp. 388-394). Cambridge, MA: MIT Press.
    • (1996) Advances in Neural Information Processing Systems , vol.8 , pp. 388-394
    • Konig, Y.1    Bourlard, H.2    Morgan, N.3
  • 26
    • 85115214750 scopus 로고
    • Hidden Markov models for labeled sequences
    • Krogh, A. (1994). Hidden Markov models for labeled sequences. In Proceedings of the 12th IAPR ICPR'94 (pp. 140-144).
    • (1994) Proceedings of the 12th IAPR ICPR'94 , pp. 140-144
    • Krogh, A.1
  • 27
  • 28
    • 0004047518 scopus 로고    scopus 로고
    • New York: Oxford University Press
    • Lauritzen, S. L. (1996). Graphical models. New York: Oxford University Press.
    • (1996) Graphical Models
    • Lauritzen, S.L.1
  • 30
    • 0025419316 scopus 로고
    • Context-dependent phonetic hidden Markov models for speaker-independent continuous speech recognition
    • Lee, K.-F. (1990). Context-dependent phonetic hidden Markov models for speaker-independent continuous speech recognition. IEEE Transactions on Acoustics, Speech and Signal Processing, 38(4), 599-609.
    • (1990) IEEE Transactions on Acoustics, Speech and Signal Processing , vol.38 , Issue.4 , pp. 599-609
    • Lee, K.-F.1
  • 33
    • 0020796537 scopus 로고
    • A decision-theoretic formulation of a training problem in speech recognition and a comparison of training by unconditional versus conditional maximum likelihood
    • Nádas, A. (1983). A decision-theoretic formulation of a training problem in speech recognition and a comparison of training by unconditional versus conditional maximum likelihood. IEEE Transactions on Acoustics, Speech and Signal Processing, 31(4), 814-817.
    • (1983) IEEE Transactions on Acoustics, Speech and Signal Processing , vol.31 , Issue.4 , pp. 814-817
    • Nádas, A.1
  • 35
    • 0024610919 scopus 로고
    • A tutorial on hidden Markov models and selected applications in speech recognition
    • Rabiner, L. R. (1989). A tutorial on hidden Markov models and selected applications in speech recognition. Proceedings of IEEE, 77(2), 257-286.
    • (1989) Proceedings of IEEE , vol.77 , Issue.2 , pp. 257-286
    • Rabiner, L.R.1
  • 38
    • 0039239710 scopus 로고    scopus 로고
    • Hidden neural networks: Application to speech recognition
    • Riis, S. K. (1998b). Hidden neural networks: Application to speech recognition. In In Proceedings of ICASSP'98 (Vol. 2, pp. 1117-1121).
    • (1998) In Proceedings of ICASSP'98 , vol.2 , pp. 1117-1121
    • Riis, S.K.1
  • 39
    • 0030672120 scopus 로고    scopus 로고
    • Hidden neural networks: A framework for HMM/NN hybrids
    • Riis, S. K., & Krogh, A. (1997). Hidden neural networks: A framework for HMM/NN hybrids. In Proceedings of ICASSP'97 (pp. 3233-3236).
    • (1997) Proceedings of ICASSP'97 , pp. 3233-3236
    • Riis, S.K.1    Krogh, A.2
  • 40
    • 0028392167 scopus 로고
    • An application of recurrent nets to phone probability estimation
    • Robinson, A. J. (1994). An application of recurrent nets to phone probability estimation. IEEE Transactions on Neural Networks, 5, 298-305.
    • (1994) IEEE Transactions on Neural Networks , vol.5 , pp. 298-305
    • Robinson, A.J.1
  • 41
    • 0022471098 scopus 로고
    • Learning representations by back-propagating errors
    • Rumelhart, D. E., Hinton, G. E., & Williams, R. J. (1986). Learning representations by back-propagating errors. Nature, 323, 533-536.
    • (1986) Nature , vol.323 , pp. 533-536
    • Rumelhart, D.E.1    Hinton, G.E.2    Williams, R.J.3
  • 42
    • 85153929881 scopus 로고
    • Boltzman chains and hidden Markov models
    • G. Tesauro, D. Touretzky, & T. Leen (Eds.), San Mateo, CA: Morgan Kaufmann
    • Saul, L. K., & Jordan, M. I. (1995). Boltzman chains and hidden Markov models. In G. Tesauro, D. Touretzky, & T. Leen (Eds.), Advances in neural information processing systems, 7 (pp. 435-442). San Mateo, CA: Morgan Kaufmann.
    • (1995) Advances in Neural Information Processing Systems , vol.7 , pp. 435-442
    • Saul, L.K.1    Jordan, M.I.2
  • 43
    • 0025627406 scopus 로고
    • The N-best algorithm: An efficient and exact procedure for finding the N most likely hypotheses
    • Schwarz, R., & Chow, Y.-L. (1990). The N-best algorithm: An efficient and exact procedure for finding the N most likely hypotheses. In Proceedings of ICASSP'90 (pp. 81-84).
    • (1990) Proceedings of ICASSP'90 , pp. 81-84
    • Schwarz, R.1    Chow, Y.-L.2
  • 44
    • 85156213225 scopus 로고    scopus 로고
    • Forward-backward retraining of recurrent neural networks
    • D. Touretzky, M. Mozer, & M. Hasselmo (Eds.), San Mateo, CA: Morgan Kaufmann
    • Senior, A., & Robinson, T. (1996). Forward-backward retraining of recurrent neural networks. In D. Touretzky, M. Mozer, & M. Hasselmo (Eds.), Advances in neural information processing dystems, 8 (pp. 743-749). San Mateo, CA: Morgan Kaufmann.
    • (1996) Advances in Neural Information Processing Dystems , vol.8 , pp. 743-749
    • Senior, A.1    Robinson, T.2
  • 45
    • 0031568356 scopus 로고    scopus 로고
    • Probabilistic independence networks for hidden Markov probability models
    • Smyth, P., Heckerman, D., & Jordan, M. I. (1997). Probabilistic independence networks for hidden Markov probability models. Neural Computation, 9, 227-269.
    • (1997) Neural Computation , vol.9 , pp. 227-269
    • Smyth, P.1    Heckerman, D.2    Jordan, M.I.3
  • 46
    • 0027166403 scopus 로고
    • Recurrent input transformations for hidden Markov models
    • Valtchev, V., Kapadia, S., & Young, S. (1993). Recurrent input transformations for hidden Markov models. In Proceedings of ICASSP'93 (pp. 287-290).
    • (1993) Proceedings of ICASSP'93 , pp. 287-290
    • Valtchev, V.1    Kapadia, S.2    Young, S.3


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