Analysis and Recognition of Asian Scripts - the State of the Art
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
FS_SFS: A novel feature selection method for support vector machines
Pattern Recognition
A new look at discriminative training for hidden Markov models
Pattern Recognition Letters
An error-counting network for pattern classification
Neurocomputing
Multiclass SVM-RFE for product form feature selection
Expert Systems with Applications: An International Journal
Application of the cross entropy method to the GLVQ algorithm
Pattern Recognition
Broad phonetic classification using discriminative Bayesian networks
Speech Communication
Probabilistic models for melodic prediction
Artificial Intelligence
Classifier combination based on confidence transformation
Pattern Recognition
Regularized margin-based conditional log-likelihood loss for prototype learning
Pattern Recognition
Discriminative training of HMMs for automatic speech recognition: A survey
Computer Speech and Language
Ensemble of feature sets and classification algorithms for sentiment classification
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
Fuzzy-decision neural networks
ICASSP'93 Proceedings of the 1993 IEEE international conference on Acoustics, speech, and signal processing: plenary, special, audio, underwater acoustics, VLSI, neural networks - Volume I
Learning in the feed-forward random neural network: A critical review
Performance Evaluation
Optimized discriminative transformations for speech features based on minimum classification error
Pattern Recognition Letters
Novel approach based feature extraction for Marathi continuous speech recognition
Proceedings of the International Conference on Advances in Computing, Communications and Informatics
HCRF-UBM approach for text-independent speaker identification
Computers & Mathematics with Applications
A comparative study of RPCL and MCE based discriminative training methods for LVCSR
IScIDE'11 Proceedings of the Second Sino-foreign-interchange conference on Intelligent Science and Intelligent Data Engineering
Discriminative GMM-HMM acoustic model selection using two-level bayesian ying-yang harmony learning
IScIDE'12 Proceedings of the third Sino-foreign-interchange conference on Intelligent Science and Intelligent Data Engineering
Handling signal variability with contextual markovian models
Pattern Recognition Letters
Joint semi-supervised learning of Hidden Conditional Random Fields and Hidden Markov Models
Pattern Recognition Letters
PEFAC - A Pitch Estimation Algorithm Robust to High Levels of Noise
IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP)
Extension of a Kernel-Based Classifier for Discriminative Spoken Keyword Spotting
Neural Processing Letters
Journal of Signal Processing Systems
Minimum Classification Error Training Incorporating Automatic Loss Smoothness Determination
Journal of Signal Processing Systems
| Hi-index | 35.69 |
A formulation is proposed for minimum-error classification, in which the misclassification probability is to be minimized based on a given set of training samples. A fundamental technique for designing a classifier that approaches the objective of minimum classification error in a more direct manner than traditional methods is given. The method is contrasted with several traditional classifier designs in typical experiments to demonstrate the superiority of the new learning formulation. The method can applied to other classifier structures as well. Experimental results pertaining to a speech recognition task are provided to show the effectiveness of the technique