In this paper we investigate the minimum classification error (MCE) criterion for the training of distance measures for template based speech recognition. These MCE-based distance measures are illustrated with example experiments on the Wall Street Journal 5k benchmark for continuous speech recognition.

This paper presents a comparative study of two discriminative methods, i.e., Rival Penalized Competitive Learning (RPCL) and Minimum Classification Error (MCE), for the tasks of Large Vocabulary Continuous Speech Recognition (LVCSR). MCE aims at minimizing a smoothed sentence error on training data, while RPCL focuses on avoiding misclassification through enforcing the learning of correct class...

Suitable medium for production of milk clotting enzyme (MCE) by Bacillus subtilis (natto) Takahashi in submerged liquid-state fermentation was screened, the nutrient factors affecting MCE production was optimized by response surface methodology. The MCE production by B. subtilis (natto) Takahashi was increased significantly by 428% in the optimal medium developed. The MCE was filtered and conce...

Climate change velocity is a vector depiction of the rate of climate displacement used for assessing climate change impacts. Interpreting velocity requires an assumption that climate trajectory length is proportional to climate change exposure; longer paths suggest greater exposure. However, distance is an imperfect measure of exposure because it does not quantify the extent to which trajectori...

The magnetocaloric effect (MCE) is an intrinsic thermal response of all magnetic solids which has a direct and strong correlation with the corresponding magnetic phase transition. It has been well recognized that the magnetic phase transition can be tuned by adjusting applied pressure. Therefore, we perform the high hydrostatic pressure magnetization measurements (up to 1.4 GPa) on a recently r...

Dimensionality reduction is an important problem in pattern recognition. I n a speech recognition system, the size of the feature set is normally large in the order of 40. Therefore, it is necessary to reduce the dimensionality of the feature space for efficient and effective speech recognition. Two popular methods to reduce the dimensionality of the feature space are Linear Discriminat Analysi...

The purpose of the study was to investigate the potential of magnetic resonance imaging (MRI) to assess transmural differences in myocardial perfusion. Contrast-enhanced MRI was performed at rest and during hyperemia in a dog model and in 22 patients with single-vessel coronary artery disease. From MR signal intensity-versus-time curves, three perfusion parameters were derived: maximum myocardi...

Feature extraction is an important component of a pattern recognition system. It performs two tasks: transforming input parameter vector into a feature vector and/or reducing its dimensionality. A well-de3ned feature extraction algorithm makes the classi3cation process more e4ective and e5cient. Two popular methods for feature extraction are linear discriminant analysis (LDA) and principal comp...

We present a new method, called the minimum cross-entropy (MCE) method for approximating the optimal solution of NP-hard combinatorial optimization problems and rare-event probability estimation, which can be viewed as an alternative to the standard cross entropy (CE) method. The MCE method presents a generic adaptive stochastic version of Kullback’s classic MinxEnt method. We discuss its simil...