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Discriminative autoencoders for acoustic modeling
Ming Han Yang
, Hung Shin Lee
, Yu Ding Lu
, Kuan Yu Chen
, Yu Tsao
,
Berlin Chen
, Hsin Min Wang
Department of Computer Science and Information Engineering
Research output
:
Contribution to journal
›
Conference article
›
peer-review
5
Citations (Scopus)
Overview
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INIS
acoustics
100%
speech
100%
modeling
100%
information
40%
data
40%
noise
40%
errors
20%
distribution
20%
implementation
20%
layers
20%
neural networks
20%
minimization
20%
Computer Science
Autoencoder
100%
Speech Recognition
50%
Neural Network
25%
Recognition Result
25%
Deep Neural Network
25%
Speech Recognition System
25%
Reconstruction Error
25%
Speaker Variability
25%
Context Dependent
25%
Acoustic Feature
25%
Engineering
Autoencoder
100%
Automatic Speech Recognition
75%
Acoustic Feature
25%
Deep Neural Network
25%
Environmental Noise
25%
Speech Data
25%
Physics
Acoustic Modeling
100%