Using bidirectional lstm recurrent neural networks to learn high-level abstractions of sequential features for automated scoring of non-native spontaneous speech.
Пожалуйста, войдите в систему, чтобы принять участие в дискуссии (добавить собственные рецензию, или комментарий)
Цитировать эту публикацию
%0 Conference Paper
%1 conf/asru/YuRSWZ0TIQ15
%A Yu, Zhou
%A Ramanarayanan, Vikram
%A Suendermann-Oeft, David
%A Wang, Xinhao
%A Zechner, Klaus
%A Chen, Lei
%A Tao, Jidong
%A Ivanou, Aliaksei
%A Qian, Yao
%B ASRU
%D 2015
%I IEEE
%K dblp
%P 338-345
%T Using bidirectional lstm recurrent neural networks to learn high-level abstractions of sequential features for automated scoring of non-native spontaneous speech.
%U http://dblp.uni-trier.de/db/conf/asru/asru2015.html#YuRSWZ0TIQ15
%@ 978-1-4799-7291-3
@inproceedings{conf/asru/YuRSWZ0TIQ15,
added-at = {2024-08-16T00:00:00.000+0200},
author = {Yu, Zhou and Ramanarayanan, Vikram and Suendermann-Oeft, David and Wang, Xinhao and Zechner, Klaus and Chen, Lei and Tao, Jidong and Ivanou, Aliaksei and Qian, Yao},
biburl = {https://www.bibsonomy.org/bibtex/2242db4f142c8b75fc67ae61fc783768f/dblp},
booktitle = {ASRU},
crossref = {conf/asru/2015},
ee = {https://doi.org/10.1109/ASRU.2015.7404814},
interhash = {ede2719d3f8e03c361f6dd0e706fbc45},
intrahash = {242db4f142c8b75fc67ae61fc783768f},
isbn = {978-1-4799-7291-3},
keywords = {dblp},
pages = {338-345},
publisher = {IEEE},
timestamp = {2024-08-19T07:44:31.000+0200},
title = {Using bidirectional lstm recurrent neural networks to learn high-level abstractions of sequential features for automated scoring of non-native spontaneous speech.},
url = {http://dblp.uni-trier.de/db/conf/asru/asru2015.html#YuRSWZ0TIQ15},
year = 2015
}