Though the statistical language modeling plays an important role in speech recognition, there are still many problems that are difficult to be solved such as the sparseness of training data. Generally, two kinds of smoothing approaches, namely the back-off model and the interpolated model, have been proposed to solve the problem of the impreciseness of language models caused by the sparseness o...

Background: Bender Gestalt Test is one of the most famous neuropsychological tests, simple and easy to perform, and is used to evaluate brain injuries. This study aimed at determining the rate of sensitivity, characteristic and cut-off point of this test in patients with traumatic brain injury (TBI). Methods and Materials: Overall, 120 TBI patients with mean age of 31.25± 13.60 years old in...

Topic tracking, which starts from a few sample stories and finds all subsequent stories that discuss the same topic, is a new challenge for the text categorization task and makes a significant contribution to the accessibility of information, such as archives of news, e-mails, and historical newspapers. Much previous research on topic tracking uses machine learning techniques. However, the smal...

This review provides the basic principle and rational for ROC analysis of rating and continuous diagnostic test results versus a gold standard. Derived indexes of accuracy, in particular area under the curve (AUC) has a meaningful interpretation for disease classification from healthy subjects. The methods of estimate of AUC and its testing in single diagnostic test and also comparative studies...

This paper reviews the current state of a Hungarian project which seeks to create a speech recognition system for the dictation of thyroid gland medical reports. First, we present the MRBA speech corpus that was assembled to support the training of general-purpose Hungarian speech recognition systems. Then we describe the processing of medical reports that were collected to help the creation of...