Phonetic feature extraction based on mutual information
نویسندگان
چکیده
منابع مشابه
Feature Extraction Based on Direct Calculation of Mutual Information
In many pattern recognition problems, it is desirable to reduce the number of input features by extracting important features related to the problems. By focusing on only the problem-relevant features, the dimension of features can be greatly reduced and thereby can result in a better generalization performance with less computational complexity. In this paper, we propose a feature extraction m...
متن کاملFeature Extraction Using Mutual Information Based on Parzen Window
In this paper, feature extraction for classification problems are dealt with. The proposed algorithm searches for a set of linear combinations of original features that maximizes the mutual information between the extracted features and the output class. The difficulties in the calculating mutual information between the extracted features and output class are resolved using Parzen window densit...
متن کاملDimension Reduction by Mutual Information Feature Extraction
During the past decades, to study high-dimensional data in a large variety of problems, researchers have proposed many Feature Extraction algorithms. One of the most effective approaches for optimal feature extraction is based on mutual information (MI). However it is not always easy to get an accurate estimation for high dimensional MI. In terms of MI, the optimal feature extraction is creatin...
متن کاملLinear feature extractors based on mutual information
This paper presents and evaluates two linear feature extractors based on mutual information. These feature extractors consider general dependencies between features and class labels, as opposed to well known linear methods such as PCA which does not consider class labels and LDA, which uses only simple low order dependencies. As evidenced by several simulations on high dimensional data sets, th...
متن کاملFeature Selection Based on Joint Mutual Information
A feature/input selection method is proposed based on joint mutual information. The new method is better than the existing methods based on mutual information in eliminating redundancy in the inputs. It is applied in a real world application to nd 2-D viewing coordinates for data visualization and to select inputs for a neural network classiier. The result shows that the new method can nd many ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: The Journal of the Acoustical Society of America
سال: 1988
ISSN: 0001-4966
DOI: 10.1121/1.2026155