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The 2015 NIST language recognition evaluation: The shared view of I2R, fantastic4 and singaMS
Kong Aik Lee
, Haizhou Li
, Li Deng
, Ville Hautamäki
, Wei Rao
, Xiong Xiao
, Anthony Larcher
, Hanwu Sun
, Trung Hieu Nguyen
, Guangsen Wang
, Aleksandr Sizov
, Jianshu Chen
, Ivan Kukanov
, Amir Hossein Poorjam
, Trung Ngo Trong
, Cheng Lin Xu
, Hai Hua Xu
, Bin Ma
, Eng Siong Chng
, Sylvain Meignier
Research output
:
Journal article publication
›
Conference article
›
Academic research
›
peer-review
20
Citations (Scopus)
Overview
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Keyphrases
Indian Institute of Technology
100%
National Institute of Standards
100%
Language Recognition
100%
Shared View
100%
Recognition System
33%
Spoken Language Recognition
33%
System Design
16%
Feature Extraction
16%
Deep Learning
16%
Deep Neural Network
16%
Recognition Technology
16%
Cepstral Features
16%
Feature Classifier
16%
Language Detection
16%
Deep Bottleneck Feature
16%
Closely Related Languages
16%
Computer Science
Spoken Language
100%
Deep Neural Network
50%
Deep Learning Method
50%
Recognition System
50%
Related Language
50%
cepstral
50%
Paradigm Shift
50%
Feature Extraction
50%
Social Sciences
Spoken Language
100%
Neural Network
50%
Psychology
Neural Network
100%