Maximum mutual information estimation of hidden Markov model parameters for speech recognition

An inequality and associated maximization technique in statistical estimation of probabilistic functions of a Markov process

Baum, L. E. (1972) · Medical Entomology and Zoology · Cited by 1,411 · see citing works

A Maximum Likelihood Approach to Continuous Speech Recognition

Bahl, L. R., Jelinek, F., & Mercer, R. L. (1983) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.1983.4767370 · Cited by 1,220 · see citing works

Some experiments with large-vocabulary isolated-word sentence recognition

Bahl, L. R., Das, S. K., de Souza, P., Jelinek, F., Katz, S., Mercer, R. L., & Picheny, M. (2005) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.1984.1172520 · Cited by 19 · see citing works

Gradient-based learning applied to document recognition

Lecun, Y., Bottou, L., Bengio, Y., & Haffner, P. (1998) · Proceedings of the IEEE · doi:10.1109/5.726791 · Cited by 58,805 · see citing works

A tutorial on hidden Markov models and selected applications in speech recognition

Rabiner, L. R. (1989) · Proceedings of the IEEE · doi:10.1109/5.18626 · Cited by 22,743 · see citing works

Deep neural networks for acoustic modeling in speech recognition: the shared views of four research groups

Hinton, G., Deng, L., Yu, D., Dahl, G., Mohamed, A.-R., Jaitly, N., Senior, A., Vanhoucke, V., Nguyen, P., Sainath, T., et al. (2012) · IEEE Signal Processing Magazine · doi:10.1109/msp.2012.2205597 · Cited by 10,260 · see citing works

Why Does Unsupervised Pre-training Help Deep Learning?

Erhan, D., Bengio, Y., Courville, A. C., Manzagol, P.-A., Vincent, P., & Samy Bengio, A. (2010) · Cited by 2,180 · see citing works

A Diversity-Promoting Objective Function for Neural Conversation Models

Li, J., Galley, M., Brockett, C., Gao, J., & Dolan, B. (2016) · Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL-HLT) · doi:10.18653/v1/n16-1014 · Cited by 1,981 · see citing works

A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition

Rabiner, L. R. (1990) · Elsevier eBooks · doi:10.1016/b978-0-08-051584-7.50027-9 · Cited by 1,868 · see citing works

Towards End-To-End Speech Recognition with Recurrent Neural Networks

Graves, A., & Jaitly, N. (2014) · Cited by 1,866 · see citing works

Deep Neural Networks for Acoustic Modeling in Speech Recognition

Hinton, G. E., Deng, L., Yu, D., Dahl, G. E., Mohamed, A., Jaitly, N., Senior, A., Vanhoucke, V., Nguyen, P., Sainath, T. N., et al. (2012) · Cited by 1,839 · see citing works

Probabilistic Interpretation of Feedforward Classification Network Outputs, with Relationships to Statistical Pattern Recognition

Bridle, J. S. (1990) · Springer eBooks · doi:10.1007/978-3-642-76153-9_28 · Cited by 1,278 · see citing works

Generation and Comprehension of Unambiguous Object Descriptions

Mao, J., Huang, J., Toshev, A., Camburu, O., Yuille, A., & Murphy, K. P. (2016) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2016.9 · Cited by 1,211 · see citing works

Connectionist Speech Recognition: A Hybrid Approach

Bourlard, H. A., & Morgan, N. H. (1993) · Infoscience (Ecole Polytechnique Fédérale de Lausanne) · Cited by 1,115 · see citing works

Hidden Markov Models for Speech Recognition

Juang, B.-H., & Rabiner, L. R. (1991) · Technometrics · doi:10.2307/1268779 · Cited by 1,069 · see citing works

Discriminative training and maximum entropy models for statistical machine translation

Och, F. J., & Ney, H. (2001) · Proceedings of the conference - Association for Computational Linguistics. Meeting · doi:10.3115/1073083.1073133 · Cited by 1,035 · see citing works

A Tutorial on Energy-Based Learning

LeCun, Y., Chopra, S., Hadsell, R. T., Ranzato, A., & Huang, F. J. (2006) · Cited by 812 · see citing works

Hidden Markov processes

Ephraim, Y., & Merhav, N. (2002) · IEEE Transactions on Information Theory · doi:10.1109/tit.2002.1003838 · Cited by 782 · see citing works

Empowering things with intelligence: a survey of the progress, challenges, and opportunities in artificial intelligence of things

Zhang, J., & Tao, D. (2021) · IEEE Internet of Things Journal · doi:10.1109/jiot.2020.3039359 · Cited by 774 · see citing works

Recent advances in the automatic recognition of audiovisual speech

Pomianos, G., Neti, C., Gravier, G., Garg, A., & Senior, A. (2003) · Proceedings of the IEEE · doi:10.1109/jproc.2003.817150 · Cited by 752 · see citing works

Multi-sensor information fusion based on machine learning for real applications in human activity recognition: State-of-the-art and research challenges

Qiu, S., Zhao, H., Jiang, N., Wang, Z., Liu, L., An, Y., Zhao, H., Miao, X., Liu, R., & Fortino, G. (2022) · Information Fusion · doi:10.1016/j.inffus.2021.11.006 · Cited by 671 · see citing works

Sequence-discriminative training of deep neural networks

Veselý, K., Ghoshal, A. K., Burget, L., & Povey, D. (2013) · Interspeech (USB) · doi:10.21437/interspeech.2013-548 · Cited by 660 · see citing works

An Introduction to Conditional Random Fields

Sutton, C. A., & McCallum, A. (2012) · Foundations and Trends® in Machine Learning · doi:10.1561/2200000013 · Cited by 624 · see citing works

Minimum Phone Error and I-smoothing for improved discriminative training

Povey, D., & Woodland, P. C. (2002) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2002.5743665 · Cited by 623 · see citing works

Minimum classification error rate methods for speech recognition

Juang, B.-H. F., Hou, W., & Lee, C. (1997) · IEEE Transactions on Speech and Audio Processing · doi:10.1109/89.568732 · Cited by 618 · see citing works

A Survey on Dialogue Systems: Recent Advances and New Frontiers

Chen, H., Liu, X., Yin, D., & Tang, J. (2017) · ACM SIGKDD Explorations Newsletter · doi:10.1145/3166054.3166058 · Cited by 579 · see citing works

An Overview of Noise-Robust Automatic Speech Recognition

Li, J., Deng, L., Gong, Y., & Haeb‐Umbach, R. (2014) · IEEE/ACM Transactions on Audio Speech and Language Processing · doi:10.1109/taslp.2014.2304637 · Cited by 568 · see citing works

The Application of Hidden Markov Models in Speech Recognition

Gales, M., & Young, S. J. (2007) · now publishers, Inc. eBooks · doi:10.1561/9781601981219 · Cited by 558 · see citing works

Translating Collocations for Bilingual Lexicons: A Statistical Approach

McKeown, K. R., Smadja, F., & Hatzivassiloglou, V. (1996) · doi:10.7916/d8c82m3r · Cited by 489 · see citing works

Self-supervised speech representation learning: A review

Mohamed, A., Lee, H.-Y., Borgholt, L., Havtorn, J. D., Edin, J., Igel, C., Kirchhoff, K., Li, S.-W., Livescu, K., Maaløe, L., et al. (2022) · IEEE Journal of Selected Topics in Signal Processing · doi:10.1109/jstsp.2022.3207050 · Cited by 372 · see citing works

Links between Markov models and multilayer perceptrons

Bourlard, H., & Wellekens, C. J. (1990) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.62605 · Cited by 350 · see citing works

A Systematic Review of Hidden Markov Models and Their Applications

Mor, B., Garhwal, S., & Kumar, A. (2020) · Archives of Computational Methods in Engineering · doi:10.1007/s11831-020-09422-4 · Cited by 343 · see citing works

Boosted MMI for model and feature-space discriminative training

Povey, D., Kanevsky, D., Kingsbury, B. E. D., Ramabhadran, B., Saon, G., & Visweswariah, K. (2008) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2008.4518545 · Cited by 342 · see citing works

Multimodal Large Language Models: A Survey

Wu, J., Gan, W., Chen, Z., Wan, S., & Yu, P. S. (2023) · IEEE International Conference on Big Data (BigData) · doi:10.1109/bigdata59044.2023.10386743 · Cited by 309 · see citing works

Unsupervised pre-trained filter learning approach for efficient convolution neural network

Rehman, S. U., Tu, S., Waqas, M. M., Huang, Y., Rehman, O. U., Ahmad, B., & Ahmad, S. (2019) · Neurocomputing · doi:10.1016/j.neucom.2019.06.084 · Cited by 271 · see citing works

Fundamentals of speech recognition

Li, J., Deng, L., Haeb‐Umbach, R., & Gong, Y. (2015) · Elsevier eBooks · doi:10.1016/b978-0-12-802398-3.00002-7 · Cited by 269 · see citing works

Neural Abstractive Text Summarization with Sequence-to-Sequence Models

Shi, T., Keneshloo, Y., Ramakrishnan, N., & Reddy, C. K. A. (2021) · ACM/IMS Transactions on Data Science · doi:10.1145/3419106 · Cited by 263 · see citing works

The Acoustic-Modeling Problem in Automatic Speech Recognition.

Brown, P. F. (1987) · doi:10.21236/ada188529 · Cited by 248 · see citing works

A Diversity-Promoting Objective Function for Neural Conversation ModelsPreprint

Li, J., Galley, M., Brockett, C., Gao, J., & Dolan, B. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1510.03055 · Cited by 242 · see citing works

Automatic modulation classification for cognitive radios using cyclic feature detection

Ramkumar, B. (2009) · IEEE Circuits and Systems Magazine · doi:10.1109/mcas.2008.931739 · Cited by 240 · see citing works

Lattice-based optimization of sequence classification criteria for neural-network acoustic modeling

Kingsbury, B. E. D. (2009) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2009.4960445 · Cited by 234 · see citing works

Automatic Speech Recognition - A Brief History of the Technology Development

Rabiner, L. R. (2004) · Cited by 233 · see citing works

Wav2Letter: an End-to-End ConvNet-based Speech Recognition SystemPreprint

Collobert, R., Puhrsch, C., & Synnaeve, G. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1609.03193 · Cited by 230 · see citing works

Connectionist probability estimators in HMM speech recognition

Renals, S. J., Morgan, N., Bourlard, H., Cohen, M., & Franco, H. (1994) · IEEE Transactions on Speech and Audio Processing · doi:10.1109/89.260359 · Cited by 228 · see citing works

Feature Learning in Deep Neural Networks - Studies on Speech Recognition TasksPreprint

Yu, D., Seltzer, M. L., Li, J., Huang, J.-T., & Seide, F. T. B. (2013) · arXiv (Cornell University) · doi:10.48550/arxiv.1301.3605 · Cited by 228 · see citing works

Off-line handwritten word recognition using a hidden Markov model type stochastic network

Chen, M.-Y., Kundu, A., & Zhou, J. W. (1994) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.291449 · Cited by 227 · see citing works

Scalable minimum Bayes risk training of deep neural network acoustic models using distributed hessian-free optimization

Kingsbury, B. E. D., Sainath, T. N., & Soltau, H. (2012) · Interspeech (USB) · doi:10.21437/interspeech.2012-3 · Cited by 222 · see citing works

Improved mispronunciation detection with deep neural network trained acoustic models and transfer learning based logistic regression classifiers

Hu, W., Qian, Y., Soong, F. K., & Wang, Y. (2015) · Speech Communication · doi:10.1016/j.specom.2014.12.008 · Cited by 201 · see citing works

An inequality for rational functions with applications to some statistical estimation problems

Gopalakrishnan, P. S., Kanevsky, D., Nadas, A. J., & Nahamoo, D. (1991) · IEEE Transactions on Information Theory · doi:10.1109/18.61108 · Cited by 197 · see citing works

Unsupervised Speech RecognitionPreprint

Baevski, A., Hsu, W.-N., Conneau, A., & Auli, M. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2105.11084 · Cited by 191 · see citing works

MMIE training of large vocabulary recognition systems

Valtchev, V., Odell, J. J., Woodland, P. C., & Young, S. J. (1997) · Speech Communication · doi:10.1016/s0167-6393(97)00029-0 · Cited by 175 · see citing works

A probabilistic approach to the understanding and training of neural network classifiers

Gish, H. (2002) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.1990.115636 · Cited by 174 · see citing works

Continuous speech recognition using hidden Markov models

Picone, J. (1990) · IEEE ASSP Magazine · doi:10.1109/53.54527 · Cited by 168 · see citing works

Pattern recognition using a family of design algorithms based upon the generalized probabilistic descent method

Katagiri, S., Juang, B.-H. F., & Lee, C. (1998) · Proceedings of the IEEE · doi:10.1109/5.726793 · Cited by 167 · see citing works

Tied mixture continuous parameter modeling for speech recognition

Bellegarda, J. R., & Nahamoo, D. (1990) · IEEE Transactions on Acoustics Speech and Signal Processing · doi:10.1109/29.61531 · Cited by 155 · see citing works

A historical perspective of speech recognition

Huang, X., Baker, J., & Reddy, R. (2014) · Communications of the ACM · doi:10.1145/2500887 · Cited by 153 · see citing works

Maximum F1-Score Discriminative Training Criterion for Automatic Mispronunciation Detection

Huang, H., Xu, H., Wang, X., & Silamu, W. (2015) · IEEE/ACM Transactions on Audio Speech and Language Processing · doi:10.1109/taslp.2015.2409733 · Cited by 149 · see citing works

Reformulating the HMM as a trajectory model by imposing explicit relationships between static and dynamic feature vector sequences

Zen, H., Tokuda, K., & Kitamura, T. (2006) · Computer Speech & Language · doi:10.1016/j.csl.2006.01.002 · Cited by 143 · see citing works

Simultaneous translation of lectures and speeches

Fügen, C., Waibel, A., & Kolss, M. (2007) · Machine Translation · doi:10.1007/s10590-008-9047-0 · Cited by 140 · see citing works

A recurrent error propagation network speech recognition system

Robinson, T., & Fallside, F. (1991) · Computer Speech & Language · doi:10.1016/0885-2308(91)90010-n · Cited by 140 · see citing works

End-to-end Speech Recognition Using Lattice-free MMI

Hadian, H., Sameti, H., Povey, D., & Khudanpur, S. P. (2018) · Interspeech (USB) · doi:10.21437/interspeech.2018-1423 · Cited by 139 · see citing works

A Review on Human-Computer Interaction and Intelligent Robots

Ren, F., & Bao, Y. (2019) · International Journal of Information Technology & Decision Making · doi:10.1142/s0219622019300052 · Cited by 134 · see citing works

Hybrid Autoregressive Transducer (HAT)

Variani, E., Rybach, D., Allauzen, C., & Riley, M. (2020) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp40776.2020.9053600 · Cited by 132 · see citing works

Interacting with computers by voice: automatic speech recognition and synthesis

O'Shaughnessy, D. (2003) · Proceedings of the IEEE · doi:10.1109/jproc.2003.817117 · Cited by 132 · see citing works

Large-Vocabulary Continuous Speech Recognition Systems: A Look at Some Recent Advances

Saon, G., & Chien, J. (2012) · IEEE Signal Processing Magazine · doi:10.1109/msp.2012.2197156 · Cited by 131 · see citing works

On adaptive decision rules and decision parameter adaptation for automatic speech recognition

Lee, C., & Huo, Q. (2000) · Proceedings of the IEEE · doi:10.1109/5.880082 · Cited by 130 · see citing works

Using LocalMaxs Algorithm for the Extraction of Contiguous and Non-contiguous Multiword Lexical Units

Silva, J., Dias, G. H., Guilloré, S., & Lopes, J. G. P. (1999) · Lecture notes in computer science · doi:10.1007/3-540-48159-1_9 · Cited by 127 · see citing works

Neural networks for statistical recognition of continuous speech

Morgan, N., & Bourlard, H. A. (1995) · Proceedings of the IEEE · doi:10.1109/5.381844 · Cited by 126 · see citing works

Large margin hidden Markov models for speech recognition

Jiang, H., Li, X., & Liu, C. (2006) · IEEE Transactions on Audio Speech and Language Processing · doi:10.1109/tasl.2006.879805 · Cited by 126 · see citing works

Advances in speech transcription at IBM under the DARPA EARS program

Chen, S. F., Kingsbury, B. E. D., Mangu, L., Povey, D., Saon, G., Soltau, H., & Zweig, G. (2006) · IEEE Transactions on Audio Speech and Language Processing · doi:10.1109/tasl.2006.879814 · Cited by 125 · see citing works

Universal Adversarial Perturbations for Speech Recognition Systems

Neekhara, P., Hussain, S., Pandey, P., Dubnov, S., McAuley, J., & Koushanfar, F. (2019) · Interspeech (USB) · doi:10.21437/interspeech.2019-1353 · Cited by 128 · see citing works

Building DNN acoustic models for large vocabulary speech recognition

Maas, A. L., Qi, P., Xie, Z., Hannun, A., Lengerich, C. T., Jurafsky, D. S., & Ng, A. Y. (2016) · Computer Speech & Language · doi:10.1016/j.csl.2016.06.007 · Cited by 120 · see citing works

Discriminative utterance verification for connected digits recognition

Rahim, M. G., Lee, C., & Juang, B.-H. F. (1997) · IEEE Transactions on Speech and Audio Processing · doi:10.1109/89.568733 · Cited by 119 · see citing works

A new algorithm for the estimation of hidden Markov model parameters

Bahl, L. R., Brown, P. F., de Souza, P. V., & Mercer, R. L. (2003) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.1988.196627 · Cited by 116 · see citing works

A machine learning approach for feature selection traffic classification using security analysis

Shafiq, M., Yu, X., Bashir, A. K., Chaudhry, H. N., & Wang, D. (2018) · The Journal of Supercomputing · doi:10.1007/s11227-018-2263-3 · Cited by 115 · see citing works

Large scale discriminative training for speech recognition

Woodland, P., & Povey, D. (2000) · Cited by 114 · see citing works

Alpha-nets: A recurrent ‘neural’ network architecture with a hidden Markov model interpretation

Bridle, J. S. (1990) · Speech Communication · doi:10.1016/0167-6393(90)90049-f · Cited by 113 · see citing works

Discriminative keyword spotting

Keshet, J., Grangier, D., & Samy Bengio, A. (2008) · Speech Communication · doi:10.1016/j.specom.2008.10.002 · Cited by 110 · see citing works

Comparison of discriminative training criteria and optimization methods for speech recognition

Schlüter, R., Macherey, W., Müller, B. P., & Ney, H. (2001) · Speech Communication · doi:10.1016/s0167-6393(00)00035-2 · Cited by 108 · see citing works

Parallel training of Deep Neural Networks with Natural Gradient and Parameter AveragingPreprint

Povey, D., Zhang, X., & Khudanpur, S. P. (2014) · arXiv (Cornell University) · Cited by 108 · see citing works

High-performance connected digit recognition using maximum mutual information estimation

Normandin, Y., Cardin, R., & Mori, R. D. (1994) · IEEE Transactions on Speech and Audio Processing · doi:10.1109/89.279279 · Cited by 107 · see citing works

Adaptive Multimodal Fusion by Uncertainty Compensation With Application to Audiovisual Speech Recognition

Papandreou, G., Katsamanis, A., Pitsikalis, V., & Maragos, P. A. (2009) · IEEE Transactions on Audio Speech and Language Processing · doi:10.1109/tasl.2008.2011515 · Cited by 101 · see citing works

Learning Speaker Representations with Mutual Information

Ravanelli, M., & Bengio, Y. (2019) · Interspeech (USB) · doi:10.21437/interspeech.2019-2380 · Cited by 90 · see citing works

Turkish Broadcast News Transcription and Retrieval

Arısoy, E., Can, D., Parlak, S., Sak, H., & Saraçlar, M. (2009) · IEEE Transactions on Audio Speech and Language Processing · doi:10.1109/tasl.2008.2012313 · Cited by 97 · see citing works

An Enhanced Stacked LSTM Method With No Random Initialization for Malware Threat Hunting in Safety and Time-Critical Systems

Jahromi, A. N., Hashemi, S., Dehghantanha, A., Parizi, R. M., & Choo, K. R. (2020) · IEEE Transactions on Emerging Topics in Computational Intelligence · doi:10.1109/tetci.2019.2910243 · Cited by 92 · see citing works

Autoregressive Hidden Markov Models for the Early Detection of Neonatal Sepsis

Stanculescu, I., Williams, C. K. I., & Freer, Y. (2014) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2013.2294692 · Cited by 92 · see citing works

Mutual Information and Diverse Decoding Improve Neural Machine TranslationPreprint

Li, J., & Jurafsky, D. (2016) · arXiv.org · doi:10.48550/arxiv.1601.00372 · Cited by 131 · see citing works

Online Arabic Handwriting Recognition Using Hidden Markov Models

Biadsy, F., El‐Sana, J., & Habash, N. Y. (2006) · doi:10.7916/d8nz8h35 · Cited by 87 · see citing works

Handwritten Chinese/Japanese Text Recognition Using Semi-Markov Conditional Random Fields

Zhou, X., Wang, D., Tian, F., Liu, C., & Nakagawa, M. (2013) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2013.49 · Cited by 86 · see citing works

Recent innovations in speech-to-text transcription at SRI-ICSI-UW

Stolcke, A., Chen, B. Y., Franco, H., Gadde, V. R. R., Graciarena, M., Hwang, M.-Y., Kirchhoff, K., Mandal, A., Morgan, N., Lei, X., et al. (2006) · IEEE Transactions on Audio Speech and Language Processing · doi:10.1109/tasl.2006.879807 · Cited by 86 · see citing works

Discriminative training of HMMs for automatic speech recognition: A survey

Jiang, H. (2009) · Computer Speech & Language · doi:10.1016/j.csl.2009.08.002 · Cited by 83 · see citing works

EMG-Based Speech Recognition Using Hidden Markov Models With Global Control Variables

Lee, K.-S. (2008) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2008.915658 · Cited by 82 · see citing works

Speech Recognition Using Augmented Conditional Random Fields

Hifny, Y., & Renals, S. J. (2009) · IEEE Transactions on Audio Speech and Language Processing · doi:10.1109/tasl.2008.2010286 · Cited by 81 · see citing works

Variable duration hidden Markov model and morphological segmentation for handwritten word recognition

Chen, M.-Y., Kundu, A., & Srihari, S. N. (1995) · IEEE Transactions on Image Processing · doi:10.1109/83.477074 · Cited by 79 · see citing works

On a model-robust training method for speech recognition

Nadas, A. J., Nahamoo, D., & Picheny, M. (1988) · IEEE Transactions on Acoustics Speech and Signal Processing · doi:10.1109/29.90371 · Cited by 79 · see citing works

A minimum discrimination information approach for hidden Markov modeling

Ephraim, Y., Dembo, A., & Rabiner, L. R. (1989) · IEEE Transactions on Information Theory · doi:10.1109/18.42209 · Cited by 76 · see citing works

Comparison of Large Margin Training to Other Discriminative Methods for Phonetic Recognition by Hidden Markov Models

Sha, F., & Saul, L. K. (2007) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.2007.366912 · Cited by 74 · see citing works

An improved MMIE training algorithm for speaker-independent, small vocabulary, continuous speech recognition

Normandin, Y., & Morgera, S. D. (1991) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.1991.150395 · Cited by 73 · see citing works

Maximum mutual information neural networks for hybrid connectionist-HMM speech recognition systems

Rigoll, G. (1994) · IEEE Transactions on Speech and Audio Processing · doi:10.1109/89.260360 · Cited by 73 · see citing works

A Unified Framework for Multilingual Speech Recognition in Air Traffic Control Systems

Lin, Y., Guo, D., Zhang, J., Chen, Z., & Yang, B. (2020) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2020.3015830 · Cited by 71 · see citing works

An Overview of Automatic Speech Recognition

Rabiner, L. R., Juang, B.-H., & Lee, C.-H. (1996) · Kluwer international series in engineering and computer science · doi:10.1007/978-1-4613-1367-0_1 · Cited by 71 · see citing works

Off-line recognition of large-set handwritten characters with multiple hidden Markov models

Park, H. S., & Lee, S.-W. (1996) · Pattern Recognition · doi:10.1016/0031-3203(95)00081-x · Cited by 71 · see citing works

On the probabilistic interpretation of neural network classifiers and discriminative training criteria

Ney, H. (1995) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.368176 · Cited by 71 · see citing works

A NEW METHOD FOR THE ESTIMATION OF HIDDEN MARKOV MODEL PARAMETERS

Uang, T., & Chen, Y. (1991) · Acta Automatica Sinica

MAXIMIZATION OF MUTUAL INFORMATION FOR TRAINING HIDDEN MARKOV MODELS IN SPEECH RECOGNITION

Giurgiu, M. (2015)

A new algorithm for the estimation of hidden Markov model parameters

Bahl, L. R., Brown, P. F., de Souza, P. V., & Mercer, R. L. (2003) · IEEE International Conference on Acoustics Speech and Signal Processing · doi:10.1109/icassp.1988.196627 · Cited by 116 · see citing works

Estimating hidden Markov model parameters so as to maximize speech recognition accuracy

Bahl, L. R., Brown, P. F., de Souza, P. V., & Mercer, R. L. (1993) · IEEE Transactions on Speech and Audio Processing · doi:10.1109/89.221369 · Cited by 56 · see citing works

Training of Hidden Markov Parameters using Mutual Information and Its Application to Speech Recognition

N.S.Kim, & Un, C. K. (1990) · 한국음향학회지= The journal of the acoustical society of Korea