Locality sensitive discriminant analysis for speaker verification

2016 ◽  
Author(s):  
Danwei Cai ◽  
Weicheng Cai ◽  
Zhidong Ni ◽  
Ming Li
Keyword(s):  
Discriminant Analysis ◽  
Speaker Verification ◽  
Locality Sensitive Discriminant Analysis

Discriminatively trained Probabilistic Linear Discriminant Analysis for speaker verification

2011 ◽  
Author(s):  
Lukas Burget ◽  
Oldrich Plchot ◽  
Sandro Cumani ◽  
Ondrej Glembek ◽  
Pavel Matejka ◽  
...  
Keyword(s):  
Discriminant Analysis ◽  
Linear Discriminant Analysis ◽  
Speaker Verification ◽  
Linear Discriminant

scholarly journals Broad Learning System with Locality Sensitive Discriminant Analysis for Hyperspectral Image Classification

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Huang Yao ◽  
Yu Zhang ◽  
Yantao Wei ◽  
Yuan Tian
Keyword(s):  
Discriminant Analysis ◽  
Manifold Learning ◽  
Hyperspectral Image ◽  
State Of The Art ◽  
Learning System ◽  
Hyperspectral Image Classification ◽  
Successful Model ◽  
Learning Tasks ◽  
Input Layer ◽  
Locality Sensitive Discriminant Analysis

In this paper, we propose a new method for hyperspectral images (HSI) classification, aiming to take advantage of both manifold learning-based feature extraction and neural networks by stacking layers applying locality sensitive discriminant analysis (LSDA) to broad learning system (BLS). BLS has been proven to be a successful model for various machine learning tasks due to its high feature representative capacity introduced by numerous randomly mapped features. However, it also produces redundancy, which is indiscriminate and finally lowers its performance and causes heavy computing demand, especially in cases of the input data bearing high dimensionality. In our work, a manifold learning method is integrated into the BLS by inserting two LSDA layers before the input layer and output layer separate, so the spectral-spatial HSI features are fully utilized to acquire the state-of-the-art classification accuracy. The extensive experiments have shown our method’s superiority.

scholarly journals Using Kernel Discriminant Analysis to Improve the Characterization of the Alternative Hypothesis for Speaker Verification

2008 ◽  
Vol 16 (8) ◽  
pp. 1675-1684 ◽  
Author(s):  
Yi-Hsiang Chao ◽  
Wei-Ho Tsai ◽  
Hsin-Min Wang ◽  
Ruei-Chuan Chang
Keyword(s):  
Discriminant Analysis ◽  
Speaker Verification ◽  
Alternative Hypothesis ◽  
Kernel Discriminant Analysis
Sign in / Sign up

Export Citation Format

Share Document