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Volumn 101, Issue 5, 2013, Pages 1054-1075

Conditional random fields in speech, audio, and language processing

Author keywords

Automatic speech recognition (ASR); natural language processing (NLP); random fields; statistical learning

Indexed keywords

NATURAL LANGUAGE PROCESSING SYSTEMS; SPEECH RECOGNITION;

EID: 84876691724     PISSN: 00189219     EISSN: None     Source Type: Journal    
DOI: 10.1109/JPROC.2013.2248112     Document Type: Review
Times cited : (32)

References (93)
  • 1
    • 0142192295 scopus 로고    scopus 로고
    • Conditional random fields: Probabilistic models for segmenting and labeling sequence data
    • Williamstown, MA, USA, Jun.
    • J. Lafferty, A. McCallum, and F. Pereira, "Conditional random fields: Probabilistic models for segmenting and labeling sequence data," in Proc. Int. Conf. Mach. Learn., Williamstown, MA, USA, Jun. 2001, pp. 282-289.
    • (2001) Proc. Int. Conf. Mach. Learn , pp. 282-289
    • Lafferty, J.1    McCallum, A.2    Pereira, F.3
  • 2
    • 79959828814 scopus 로고    scopus 로고
    • Deep-structured hidden conditional random fields for phonetic recognition
    • Makuhari, Chiba, Japan, Sep.
    • D. Yu and L. Deng, "Deep-structured hidden conditional random fields for phonetic recognition," in Proc. Annu. Conf. Int. Speech Commun. Assoc., Makuhari, Chiba, Japan, Sep. 2010, pp. 2986-2989.
    • (2010) Proc. Annu. Conf. Int. Speech Commun. Assoc , pp. 2986-2989
    • Yu, D.1    Deng, L.2
  • 3
    • 33750032384 scopus 로고    scopus 로고
    • An introduction to conditional random fields for relational learning
    • L. Getoor and B. Taskar, Eds. Cambridge, MA, USA: MIT Press
    • C. Sutton and A. McCallum, "An introduction to conditional random fields for relational learning," in Introduction to Statistical Relational Learning, L. Getoor and B. Taskar, Eds. Cambridge, MA, USA: MIT Press, 2007, pp. 93-128.
    • (2007) Introduction to Statistical Relational Learning , pp. 93-128
    • Sutton, C.1    McCallum, A.2
  • 6
    • 0024610919 scopus 로고
    • A tutorial on hidden Markov models and selected applications in speech recognition
    • Feb.
    • L. R. Rabiner, "A tutorial on hidden Markov models and selected applications in speech recognition," Proc. IEEE, vol. 77, no. 2, pp. 257-286, Feb. 1989.
    • (1989) Proc. IEEE , vol.77 , Issue.2 , pp. 257-286
    • Rabiner, L.R.1
  • 7
    • 0000747663 scopus 로고    scopus 로고
    • Maximum entropy Markov models for information extraction and segmentation
    • Stanford, CA, USA, Jun.
    • A. McCallum, D. Freitag, and F. Pereira, "Maximum entropy Markov models for information extraction and segmentation," in Proc. Int. Conf. Mach. Learn., Stanford, CA, USA, Jun. 2000, pp. 591-598.
    • (2000) Proc. Int. Conf. Mach. Learn , pp. 591-598
    • McCallum, A.1    Freitag, D.2    Pereira, F.3
  • 8
    • 84876675500 scopus 로고    scopus 로고
    • Introduction to classification: Likelihoods, margins, features, and kernels
    • Rochester, NY, USA, Apr.
    • D. Klein, "Introduction to classification: Likelihoods, margins, features, and kernels," in Proc. Human Lang. Technol. Conf. NAACLVTut., Rochester, NY, USA, Apr. 2007.
    • (2007) Proc. Human Lang. Technol. Conf. NAACLVTut
    • Klein, D.1
  • 11
    • 33947615175 scopus 로고    scopus 로고
    • Dynamic conditional random fields: Factorized probabilistic models for labeling and segmenting sequence data
    • Mar.
    • C. Sutton, A. McCallum, and K. Rohanimanesh, "Dynamic conditional random fields: Factorized probabilistic models for labeling and segmenting sequence data," J. Mach. Learn. Res., vol. 8, pp. 693-723, Mar. 2007.
    • (2007) J. Mach. Learn. Res. , vol.8 , pp. 693-723
    • Sutton, C.1    McCallum, A.2    Rohanimanesh, K.3
  • 15
    • 70350435251 scopus 로고    scopus 로고
    • Speech recognition using augmented conditional random fields
    • Feb.
    • Y. Hifny and S. Renals, "Speech recognition using augmented conditional random fields," IEEE Trans. Audio Speech Lang. Process., vol. 17, no. 2, pp. 354-365, Feb. 2009.
    • (2009) IEEE Trans. Audio Speech Lang. Process. , vol.17 , Issue.2 , pp. 354-365
    • Hifny, Y.1    Renals, S.2
  • 16
    • 0002652285 scopus 로고    scopus 로고
    • A maximum entropy approach to natural language processing
    • Mar.
    • A. L. Berger, S. D. Della Pietra, and V. J. D. Della Pietra, "A maximum entropy approach to natural language processing," Comput. Linguist., vol. 22, no. 1, pp. 39-71, Mar. 1996.
    • (1996) Comput. Linguist. , vol.22 , Issue.1 , pp. 39-71
    • Berger, A.L.1    Della Pietra, S.D.2    Della Pietra, V.J.D.3
  • 18
    • 0000732463 scopus 로고
    • A limited memory algorithm for bound constrained optimization
    • Sep.
    • R. H. Byrd, P. Lu, J. Nocedal, and C. Y. Zhu, "A limited memory algorithm for bound constrained optimization," SIAM J. Sci. Comput., vol. 16, no. 6, pp. 1190-1208, Sep. 1995.
    • (1995) SIAM J. Sci. Comput. , vol.16 , Issue.6 , pp. 1190-1208
    • Byrd, R.H.1    Lu, P.2    Nocedal, J.3    Zhu, C.Y.4
  • 19
    • 84943274699 scopus 로고
    • A direct adaptive method for faster backpropagation learning: The RPROP algorithm
    • San Francisco, CA, USA, Mar.
    • M. Riedmiller and H. Braun, "A direct adaptive method for faster backpropagation learning: The RPROP algorithm," in Proc. IEEE Int. Conf. Neural Netw., San Francisco, CA, USA, Mar. 1993, vol. 1, pp. 586-591.
    • (1993) Proc. IEEE Int. Conf. Neural Netw , vol.1 , pp. 586-591
    • Riedmiller, M.1    Braun, H.2
  • 20
    • 77949370075 scopus 로고    scopus 로고
    • A segmental CRF approach to large vocabulary continuous speech recognition
    • Merano, Italy, Dec.
    • G. Zweig and P. Nguyen, "A segmental CRF approach to large vocabulary continuous speech recognition," in Proc. IEEE Workshop Autom. Speech Recognit. Understand., Merano, Italy, Dec. 2009, pp. 152-157.
    • (2009) Proc. IEEE Workshop Autom. Speech Recognit. Understand , pp. 152-157
    • Zweig, G.1    Nguyen, P.2
  • 21
    • 85032750905 scopus 로고    scopus 로고
    • Discriminative learning in sequential pattern recognition
    • Sep.
    • X. He, L. Deng, and W. Chou, "Discriminative learning in sequential pattern recognition," IEEE Signal Process. Mag., vol. 25, no. 5, pp. 14-36, Sep. 2008.
    • (2008) IEEE Signal Process. Mag. , vol.25 , Issue.5 , pp. 14-36
    • He, X.1    Deng, L.2    Chou, W.3
  • 22
    • 84876678601 scopus 로고    scopus 로고
    • Discriminative trainingVFundamentals and applications
    • Makuhari, Chiba, Japan, Sep.
    • C.-H. Lee, "Discriminative trainingVFundamentals and applications," presented at the Interspeech Tut. Session, Makuhari, Chiba, Japan, Sep. 2010.
    • (2010) Presented at the Interspeech Tut. Session
    • Lee, C.-H.1
  • 23
    • 85127836544 scopus 로고    scopus 로고
    • Discriminative training methods for hidden Markov models: Theory and experiments with perceptron algorithms
    • Prague, Czech Republic, Jul.
    • M. Collins, "Discriminative training methods for hidden Markov models: Theory and experiments with perceptron algorithms," in Proc. Conf. Empirical Methods Natural Lang. Process., Prague, Czech Republic, Jul. 2002, pp. 1-8.
    • (2002) Proc. Conf. Empirical Methods Natural Lang. Process , pp. 1-8
    • Collins, M.1
  • 24
    • 84860500490 scopus 로고    scopus 로고
    • Training conditional random fields with multivariate evaluation measures
    • Sydney, Australia, Jul.
    • J. Suzuki, E. McDermott, and H. Isozaki, "Training conditional random fields with multivariate evaluation measures," in Proc. Annu. Meeting Assoc. Comput. Linguist., Sydney, Australia, Jul. 2006, pp. 217-224.
    • (2006) Proc. Annu. Meeting Assoc. Comput. Linguist , pp. 217-224
    • Suzuki, J.1    McDermott, E.2    Isozaki, H.3
  • 25
    • 0036296863 scopus 로고    scopus 로고
    • Minimum phone error and I-smoothing for improved discriminative training
    • May
    • D. Povey and P. Woodland, "Minimum phone error and I-smoothing for improved discriminative training," in Proc. IEEE Int. Conf. Acoust. Speech Signal Process., May 2002, vol. 1, pp. 105-108.
    • (2002) Proc. IEEE Int. Conf. Acoust. Speech Signal Process , vol.1 , pp. 105-108
    • Povey, D.1    Woodland, P.2
  • 26
    • 55549127511 scopus 로고    scopus 로고
    • Minimum tag error for discriminative training of conditional random fields
    • Jan.
    • Y. Xiong, J. Zhu, H. Huang, and H. Xu, "Minimum tag error for discriminative training of conditional random fields," Inf. Sci., vol. 179, no. 1-2, pp. 169-179, Jan. 2009.
    • (2009) Inf. Sci. , vol.179 , Issue.1-2 , pp. 169-179
    • Xiong, Y.1    Zhu, J.2    Huang, H.3    Xu, H.4
  • 27
    • 77953614269 scopus 로고    scopus 로고
    • Large margin cost-sensitive learning of conditional random fields
    • M. Kim. (2010). Large margin cost-sensitive learning of conditional random fields. Pattern Recognit. [Online]. 43(10), pp. 3683-3692. Available: http://www.sciencedirect.com/science/article/pii/S0031320310002141
    • (2010) Pattern Recognit. [Online]. , vol.43 , Issue.10 , pp. 3683-3692
    • Kim, M.1
  • 28
    • 85124016637 scopus 로고    scopus 로고
    • A maximum entropy model for part-of-speech tagging
    • E. Brill and K. Church, Eds., Somerset, NJ, USA, May
    • A. Ratnaparkhi, "A maximum entropy model for part-of-speech tagging," in Proc. Conf. Empirical Methods Natural Lang. Process., E. Brill and K. Church, Eds., Somerset, NJ, USA, May 1996, pp. 133-142.
    • (1996) Proc. Conf. Empirical Methods Natural Lang. Process , pp. 133-142
    • Ratnaparkhi, A.1
  • 29
    • 33646907991 scopus 로고    scopus 로고
    • Two decades of statistical language modeling: Where do we go from here?"
    • Aug.
    • R. Rosenfeld, "Two decades of statistical language modeling: Where do we go from here?" Proc. IEEE, vol. 88, no. 8, pp. 1270-1278, Aug. 2000.
    • (2000) Proc. IEEE , vol.88 , Issue.8 , pp. 1270-1278
    • Rosenfeld, R.1
  • 30
    • 73649117102 scopus 로고    scopus 로고
    • Joint acoustic and language modeling for speech recognition
    • Mar.
    • J. Chien and C. Chueh, "Joint acoustic and language modeling for speech recognition," Speech Commun., vol. 52, no. 3, pp. 223-235, Mar. 2010.
    • (2010) Speech Commun. , vol.52 , Issue.3 , pp. 223-235
    • Chien, J.1    Chueh, C.2
  • 31
    • 33947702666 scopus 로고    scopus 로고
    • Augmented statistical models for speech recognition
    • Toulouse, France, May
    • M. I. Layton and M. J. F. Gales, "Augmented statistical models for speech recognition," in Proc. IEEE Int. Conf. Acoust. Speech Signal Process., Toulouse, France, May 2006, vol. 1, pp. 129-132.
    • (2006) Proc. IEEE Int. Conf. Acoust. Speech Signal Process , vol.1 , pp. 129-132
    • Layton, M.I.1    Gales, M.J.F.2
  • 33
    • 64849090489 scopus 로고    scopus 로고
    • Conditional random fields for integrating local discriminative classifiers
    • Mar.
    • J. Morris and E. Fosler-Lussier, "Conditional random fields for integrating local discriminative classifiers," IEEE Trans. Audio Speech Lang. Process., vol. 16, no. 3, pp. 617-628, Mar. 2008.
    • (2008) IEEE Trans. Audio Speech Lang. Process. , vol.16 , Issue.3 , pp. 617-628
    • Morris, J.1    Fosler-Lussier, E.2
  • 34
    • 79956277935 scopus 로고    scopus 로고
    • Learning a discriminative weighted finite-state transducer for speech recognition
    • Jul.
    • M. Lehr and I. Shafran, "Learning a discriminative weighted finite-state transducer for speech recognition," IEEE Trans. Audio Speech Lang. Process., vol. 19, no. 5, pp. 1360-1367, Jul. 2011.
    • (2011) IEEE Trans. Audio Speech Lang. Process. , vol.19 , Issue.5 , pp. 1360-1367
    • Lehr, M.1    Shafran, I.2
  • 35
    • 85149106909 scopus 로고    scopus 로고
    • Discriminative language modeling with conditional random fields and the perceptron algorithm
    • Barcelona, Spain, Jul.
    • B. Roark, M. Saraclar, M. Collins, and M. Johnson, "Discriminative language modeling with conditional random fields and the perceptron algorithm," in Proc. Annu. Meeting Assoc. Comput. Linguist., Barcelona, Spain, Jul. 2004, pp. 47-54.
    • (2004) Proc. Annu. Meeting Assoc. Comput. Linguist , pp. 47-54
    • Roark, B.1    Saraclar, M.2    Collins, M.3    Johnson, M.4
  • 36
    • 84865213310 scopus 로고    scopus 로고
    • Decoding network optimization using minimum transition error training
    • Kyoto, Japan, Mar.
    • Y. Kubo, S. Watanabe, and A. Nakamura, "Decoding network optimization using minimum transition error training," in Proc. IEEE Int. Conf. Acoust. Speech Signal Process., Kyoto, Japan, Mar. 2012, pp. 4197-4200.
    • (2012) Proc. IEEE Int. Conf. Acoust. Speech Signal Process , pp. 4197-4200
    • Kubo, Y.1    Watanabe, S.2    Nakamura, A.3
  • 38
    • 84867598637 scopus 로고    scopus 로고
    • Classification and recognition with direct segment models
    • Kyoto, Japan, Mar.
    • G. Zweig, "Classification and recognition with direct segment models," in Proc. IEEE Int. Conf. Acoust. Speech Signal Process., Kyoto, Japan, Mar. 2012, pp. 4161-4164.
    • (2012) Proc. IEEE Int. Conf. Acoust. Speech Signal Process , pp. 4161-4164
    • Zweig, G.1
  • 40
    • 33646426783 scopus 로고    scopus 로고
    • Kernel conditional random fields: Representation and clique selection
    • Banff, AB, Canada, Jul.
    • J. Lafferty, X. Zhu, and Y. Liu, "Kernel conditional random fields: Representation and clique selection," in Proc. Int. Conf. Mach. Learn., Banff, AB, Canada, Jul. 2004, pp. 64-71.
    • (2004) Proc. Int. Conf. Mach. Learn , pp. 64-71
    • Lafferty, J.1    Zhu, X.2    Liu, Y.3
  • 41
    • 84863373241 scopus 로고    scopus 로고
    • Conditional neural fields
    • Vancouver, BC, Canada, Dec.
    • J. Peng, L. Bo, and J. Xu, "Conditional neural fields," in Proc. Adv. Neural Inf. Process. Syst., Vancouver, BC, Canada, Dec. 2009, pp. 1419-1427.
    • (2009) Proc. Adv. Neural Inf. Process. Syst , pp. 1419-1427
    • Peng, J.1    Bo, L.2    Xu, J.3
  • 42
    • 78049406405 scopus 로고    scopus 로고
    • Backpropagation training for multilayer conditional random field based phone recognition
    • Dallas, TX, USA, Mar.
    • R. Prabhavalkar and E. Fosler-Lussier, "Backpropagation training for multilayer conditional random field based phone recognition," in Proc. IEEE Int. Conf. Acoust. Speech Signal Process., Dallas, TX, USA, Mar. 2010, pp. 5534-5537.
    • (2010) Proc. IEEE Int. Conf. Acoust. Speech Signal Process , pp. 5534-5537
    • Prabhavalkar, R.1    Fosler-Lussier, E.2
  • 43
    • 80051660406 scopus 로고    scopus 로고
    • Automatic speech recognition using hidden conditional neural fields
    • Prague, Czech Republic, May
    • Y. Fujii, K. Yamamoto, and S. Nakagawa, "Automatic speech recognition using hidden conditional neural fields," in Proc. IEEE Int. Conf. Acoust. Speech Signal Process., Prague, Czech Republic, May 2011, pp. 5036-5039.
    • (2011) Proc. IEEE Int. Conf. Acoust. Speech Signal Process , pp. 5036-5039
    • Fujii, Y.1    Yamamoto, K.2    Nakagawa, S.3
  • 44
    • 70349213445 scopus 로고    scopus 로고
    • Lattice-based optimization of sequence classification criteria for neural-network acoustic modeling
    • Taipei, Taiwan, Apr.
    • B. Kingsbury, "Lattice-based optimization of sequence classification criteria for neural-network acoustic modeling," in Proc. IEEE Int. Conf. Acoust. Speech Signal Process., Taipei, Taiwan, Apr. 2009, pp. 3761-3764.
    • (2009) Proc. IEEE Int. Conf. Acoust. Speech Signal Process , pp. 3761-3764
    • Kingsbury, B.1
  • 45
    • 33745805403 scopus 로고    scopus 로고
    • A fast learning algorithm for deep belief nets
    • May
    • G. E. Hinton, S. Osindero, and Y.-W. Teh, "A fast learning algorithm for deep belief nets," Neural Comput., vol. 18, no. 7, pp. 1527-1554, May 2006.
    • (2006) Neural Comput. , vol.18 , Issue.7 , pp. 1527-1554
    • Hinton, G.E.1    Osindero, S.2    Teh, Y.-W.3
  • 46
    • 78649308591 scopus 로고    scopus 로고
    • Sequential labeling using deep-structured conditional random fields
    • Dec.
    • D. Yu, S. Wang, and L. Deng, "Sequential labeling using deep-structured conditional random fields," IEEE J. Sel. Top. Signal Process., vol. 4, no. 6, pp. 965-973, Dec. 2010.
    • (2010) IEEE J. Sel. Top. Signal Process. , vol.4 , Issue.6 , pp. 965-973
    • Yu, D.1    Wang, S.2    Deng, L.3
  • 47
    • 85162533997 scopus 로고    scopus 로고
    • A convergence analysis of log-linear training
    • J. Shawe-Taylor, R. Zemel, P. Bartlett, F. Pereira, and K. Weinberger, Eds., Granada, Spain, Mar.
    • S. Wiesler and H. Ney, "A convergence analysis of log-linear training," in Proc. Adv. Neural Inf. Process. Syst., J. Shawe-Taylor, R. Zemel, P. Bartlett, F. Pereira, and K. Weinberger, Eds., Granada, Spain, Mar. 2011, pp. 657-665.
    • (2011) Proc. Adv. Neural Inf. Process. Syst , pp. 657-665
    • Wiesler, S.1    Ney, H.2
  • 50
    • 24944537843 scopus 로고    scopus 로고
    • Large margin methods for structured and interdependent output variables
    • Sep.
    • I. Tsochantaridis, T. Joachims, T. Hofmann, and Y. Altun, "Large margin methods for structured and interdependent output variables," J. Mach. Learn. Res., vol. 6, pp. 1453-1484, Sep. 2005.
    • (2005) J. Mach. Learn. Res. , vol.6 , pp. 1453-1484
    • Tsochantaridis, I.1    Joachims, T.2    Hofmann, T.3    Altun, Y.4
  • 52
    • 85032751545 scopus 로고    scopus 로고
    • Structured discriminative models for speech recognition
    • Nov.
    • M. Gales, S. Watanabe, and E. Fosler-Lussier, "Structured discriminative models for speech recognition," Signal Process. Mag., vol. 29, no. 6, pp. 70-81, Nov. 2012.
    • (2012) Signal Process. Mag. , vol.29 , Issue.6 , pp. 70-81
    • Gales, M.1    Watanabe, S.2    Fosler-Lussier, E.3
  • 54
    • 0013288412 scopus 로고    scopus 로고
    • Ph.D. dissertation, Comput. Sci. Div., Dept. Electr. Eng. Comput. Sci., Univ. California, Berkeley, CA, USA
    • K. P. Murphy, "Dynamic Bayesian networks: Representation, inference and learning," Ph.D. dissertation, Comput. Sci. Div., Dept. Electr. Eng. Comput. Sci., Univ. California, Berkeley, CA, USA, 2002.
    • (2002) Dynamic Bayesian Networks: Representation, Inference and Learning
    • Murphy, K.P.1
  • 55
    • 70450164028 scopus 로고    scopus 로고
    • Monaural segregation of voiced speech using discriminative random fields
    • Brighton, U.K., Sep.
    • R. Prabhavalkar, Z. Jin, and E. Fosler-Lussier, "Monaural segregation of voiced speech using discriminative random fields," in Proc. Annu. Conf. Int. Speech Commun. Assoc., Brighton, U.K., Sep. 2009, pp. 856-859.
    • (2009) Proc. Annu. Conf. Int. Speech Commun. Assoc , pp. 856-859
    • Prabhavalkar, R.1    Jin, Z.2    Fosler-Lussier, E.3
  • 56
    • 0035246564 scopus 로고    scopus 로고
    • Factor graphs and the sum-product algorithm
    • Feb.
    • F. R. Kschischang, B. J. Frey, and H. A. Loeliger, "Factor graphs and the sum-product algorithm," IEEE Trans. Inf. Theory, vol. 47, no. 2, pp. 498-519, Feb. 2001.
    • (2001) IEEE Trans. Inf. Theory , vol.47 , Issue.2 , pp. 498-519
    • Kschischang, F.R.1    Frey, B.J.2    Loeliger, H.A.3
  • 57
    • 46149134436 scopus 로고
    • Fusion, propagation, and structuring in belief networks
    • Sep.
    • J. Pearl, "Fusion, propagation, and structuring in belief networks," Artif. Intell., vol. 29, no. 3, pp. 241-288, Sep. 1986.
    • (1986) Artif. Intell. , vol.29 , Issue.3 , pp. 241-288
    • Pearl, J.1
  • 58
    • 0002425879 scopus 로고    scopus 로고
    • Loopy belief propagation for approximate inference: An empirical study
    • Stockholm, Sweden, Jul.
    • K. P. Murphy, Y. Weiss, and M. I. Jordan, "Loopy belief propagation for approximate inference: An empirical study," in Proc. Int. Conf. Uncertainty Artif. Intell., Stockholm, Sweden, Jul. 1999, pp. 467-475.
    • (1999) Proc. Int. Conf. Uncertainty Artif. Intell , pp. 467-475
    • Murphy, K.P.1    Weiss, Y.2    Jordan, M.I.3
  • 59
    • 0033225865 scopus 로고    scopus 로고
    • An introduction to variational methods for graphical models
    • Nov.
    • M. I. Jordan, Z. Ghahramani, T. S. Jaakkola, and L. K. Saul, "An introduction to variational methods for graphical models," Mach. Learn., vol. 37, no. 2, pp. 183-233, Nov. 1999.
    • (1999) Mach. Learn. , vol.37 , Issue.2 , pp. 183-233
    • Jordan, M.I.1    Ghahramani, Z.2    Jaakkola, T.S.3    Saul, L.K.4
  • 60
    • 65749118363 scopus 로고    scopus 로고
    • Graphical models, exponential families, and variational inference
    • Jan.
    • M. J. Wainwright and M. I. Jordan, "Graphical models, exponential families, and variational inference," Found. Trends Mach. Learn., vol. 1, no. 1-2, pp. 1-305, Jan. 2008.
    • (2008) Found. Trends Mach. Learn. , vol.1 , Issue.1-2 , pp. 1-305
    • Wainwright, M.J.1    Jordan, M.I.2
  • 63
    • 0002629270 scopus 로고
    • Maximum likelihood from incomplete data via the em algorithm
    • A. P. Dempster, N. M. Laird, and D. B. Rubin, "Maximum likelihood from incomplete data via the EM algorithm," J. Roy. Stat. Soc., vol. 39, no. 1, pp. 1-38, 1977.
    • (1977) J. Roy. Stat. Soc. , vol.39 , Issue.1 , pp. 1-38
    • Dempster, A.P.1    Laird, N.M.2    Rubin, D.B.3
  • 64
    • 34047192804 scopus 로고    scopus 로고
    • Semi-Markov conditional random fields for information extraction
    • Vancouver, BC, Canada, Dec.
    • S. Sarawagi and W. W. Cohen, "Semi-Markov conditional random fields for information extraction," in Proc. Adv. Neural Inf. Process. Syst., Vancouver, BC, Canada, Dec. 2004, pp. 1185-1192.
    • (2004) Proc. Adv. Neural Inf. Process. Syst , pp. 1185-1192
    • Sarawagi, S.1    Cohen, W.W.2
  • 65
    • 84878565391 scopus 로고    scopus 로고
    • Efficient segmental conditional random fields for phone recognition
    • Portland, OR, USA, Sep.
    • Y. He and E. Fosler-Lussier, "Efficient segmental conditional random fields for phone recognition," in Proc. Annu. Conf. Int. Speech Commun. Assoc., Portland, OR, USA, Sep. 2012, pp. 1898-1901.
    • (2012) Proc. Annu. Conf. Int. Speech Commun. Assoc , pp. 1898-1901
    • He, Y.1    Fosler-Lussier, E.2
  • 66
    • 69849092237 scopus 로고    scopus 로고
    • M.S. thesis, Dept. Electr. Eng. Comput. Sci., Massachusetts Inst. Technol. (MIT), Cambridge, MA, USA
    • P. Liang, "Semi-supervised learning for natural language," M.S. thesis, Dept. Electr. Eng. Comput. Sci., Massachusetts Inst. Technol. (MIT), Cambridge, MA, USA, 2005.
    • (2005) Semi-supervised Learning for Natural Language
    • Liang, P.1
  • 67
    • 80053343111 scopus 로고    scopus 로고
    • A hybrid Markov/semi-Markov conditional random field for sequence segmentation
    • Sydney, Australia, Jul.
    • G. Andrew, "A hybrid Markov/semi-Markov conditional random field for sequence segmentation," in Proc. Conf. Empirical Methods Natural Lang. Process., Sydney, Australia, Jul. 2006, pp. 465-472.
    • (2006) Proc. Conf. Empirical Methods Natural Lang. Process , pp. 465-472
    • Andrew, G.1
  • 70
    • 0026982122 scopus 로고
    • Discriminative learning for minimum error classification
    • Dec.
    • B. H. Juang and S. Katagiri, "Discriminative learning for minimum error classification," IEEE Trans. Signal Process., vol. 40, no. 12, pp. 3043-3054, Dec. 1992.
    • (1992) IEEE Trans. Signal Process. , vol.40 , Issue.12 , pp. 3043-3054
    • Juang, B.H.1    Katagiri, S.2
  • 75
    • 0000583248 scopus 로고
    • Probabilistic interpretation of feedforward classification network outputs, with relationships to statistical pattern recognition
    • Fogelman-Soulie and Herault, Eds. New York, NY, USA: Springer-Verlag
    • J. S. Bridle, "Probabilistic interpretation of feedforward classification network outputs, with relationships to statistical pattern recognition," in Neurocomputing: Algorithms, Architectures and Applications, Fogelman-Soulie and Herault, Eds. New York, NY, USA: Springer-Verlag, 1990, pp. 227-236.
    • (1990) Neurocomputing: Algorithms, Architectures and Applications , pp. 227-236
    • Bridle, J.S.1
  • 76
    • 84910103509 scopus 로고
    • REMAP: Recursive estimation and maximization of a posteriori probabilitiesVApplication to transition-based connectionist speech recognition
    • Denver, CO, USA, Nov.
    • Y. Konig, H. Bourlard, and N. Morgan, "REMAP: Recursive estimation and maximization of a posteriori probabilitiesVApplication to transition-based connectionist speech recognition," in Proc. Adv. Neural Inf. Process. Syst., Denver, CO, USA, Nov. 1995, pp. 388-394.
    • (1995) Proc. Adv. Neural Inf. Process. Syst , pp. 388-394
    • Konig, Y.1    Bourlard, H.2    Morgan, N.3
  • 77
    • 84880862726 scopus 로고    scopus 로고
    • A dual-layer CRFs based joint decoding method for cascaded segmentation and labeling tasks
    • Hyderabad, India, Jan.
    • Y. Shi and M. Wang, "A dual-layer CRFs based joint decoding method for cascaded segmentation and labeling tasks," in Proc. Int. Joint Conf. Artif. Intell., Hyderabad, India, Jan. 2007, pp. 1707-1712.
    • (2007) Proc. Int. Joint Conf. Artif. Intell , pp. 1707-1712
    • Shi, Y.1    Wang, M.2
  • 79
    • 85111262831 scopus 로고    scopus 로고
    • Applying conditional random fields to Japanese morphological analysis
    • Barcelona, Catalunya, Spain, Jul.
    • T. Kudo, K. Yamamoto, and Y. Matsumoto, "Applying conditional random fields to Japanese morphological analysis," in Proc. Conf. Empirical Methods Natural Lang. Process., Barcelona, Catalunya, Spain, Jul. 2004, pp. 230-237.
    • (2004) Proc. Conf. Empirical Methods Natural Lang. Process , pp. 230-237
    • Kudo, T.1    Yamamoto, K.2    Matsumoto, Y.3
  • 80
    • 85121365374 scopus 로고    scopus 로고
    • Early results for named entity recognition with conditional random fields, feature induction and web-enhanced lexicons
    • Edmonton, AB, Canada, May
    • A. McCallum and W. Li, "Early results for named entity recognition with conditional random fields, feature induction and web-enhanced lexicons," in Proc. Conf. Natural Lang. Learn., Edmonton, AB, Canada, May 2003, pp. 188-191.
    • (2003) Proc. Conf. Natural Lang. Learn , pp. 188-191
    • McCallum, A.1    Li, W.2
  • 81
    • 84859918687 scopus 로고    scopus 로고
    • Incorporating non-local information into information extraction systems by Gibbs sampling
    • Ann Arbor, MI, USA, Jun.
    • J. Finkel, T. Grenager, and C. Manning, "Incorporating non-local information into information extraction systems by Gibbs sampling," in Proc. Annu. Meeting Assoc. Comput. Linguist., Ann Arbor, MI, USA, Jun. 2005, pp. 363-370.
    • (2005) Proc. Annu. Meeting Assoc. Comput. Linguist , pp. 363-370
    • Finkel, J.1    Grenager, T.2    Manning, C.3
  • 87
    • 70450209946 scopus 로고    scopus 로고
    • Crandem: Conditional random fields for word recognition
    • Brighton, U.K., Sep.
    • J. Morris and E. Fosler-Lussier, "Crandem: Conditional random fields for word recognition," in Proc. Annu. Conf. Int. Speech Commun. Assoc., Brighton, U.K., Sep. 2009, pp. 3063-3066.
    • (2009) Proc. Annu. Conf. Int. Speech Commun. Assoc , pp. 3063-3066
    • Morris, J.1    Fosler-Lussier, E.2
  • 89
    • 78650966704 scopus 로고    scopus 로고
    • Letter-to-sound pronunciation prediction using conditional random fields
    • Feb.
    • D. Wang and S. King, "Letter-to-sound pronunciation prediction using conditional random fields," IEEE Signal Process. Lett., vol. 18, no. 2, pp. 122-125, Feb. 2011.
    • (2011) IEEE Signal Process. Lett. , vol.18 , Issue.2 , pp. 122-125
    • Wang, D.1    King, S.2
  • 91
    • 84892233308 scopus 로고    scopus 로고
    • On ideal binary mask as the computational goal of auditory scene analysis
    • P. Divenyi, Ed. New York, NY, USA: Springer-Verlag
    • D. Wang, "On ideal binary mask as the computational goal of auditory scene analysis," in Speech Separation by Humans and Machines, P. Divenyi, Ed. New York, NY, USA: Springer-Verlag, 2005, pp. 181-197.
    • (2005) Speech Separation by Humans and Machines , pp. 181-197
    • Wang, D.1
  • 92
    • 80052630625 scopus 로고    scopus 로고
    • A conditional random field framework for robust and scalable audio-to-score matching
    • Nov.
    • C. Joder, S. Essid, and G. Richard, "A conditional random field framework for robust and scalable audio-to-score matching," IEEE Trans. Audio Speech Lang. Process., vol. 19, no. 8, pp. 2385-2397, Nov. 2011.
    • (2011) IEEE Trans. Audio Speech Lang. Process. , vol.19 , Issue.8 , pp. 2385-2397
    • Joder, C.1    Essid, S.2    Richard, G.3
  • 93
    • 80053041569 scopus 로고    scopus 로고
    • Joint multi-pitch detection using harmonic envelope estimation for polyphonic music transcription
    • Oct.
    • E. Benetos and S. Dixon, "Joint multi-pitch detection using harmonic envelope estimation for polyphonic music transcription," IEEE J. Sel. Top. Signal Process., vol. 5, no. 6, pp. 1111-1123, Oct. 2011.
    • (2011) IEEE J. Sel. Top. Signal Process. , vol.5 , Issue.6 , pp. 1111-1123
    • Benetos, E.1    Dixon, S.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.