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Paper Abstract and Keywords
Presentation 2015-08-21 10:00
Latent Words Recurrent Neural Network Language Models for Automatic Speech Recognition
Ryo Masumura, Taichi Asami, Takanobu Oba, Hirokazu Masataki, Sumitaka Sakauchi (NTT), Akinori Ito (Tohoku Universicty) SP2015-50
Abstract (in Japanese) (See Japanese page) 
(in English) This paper proposes a novel language modeling approach called latent word recurrent neural network language model, which solves the problems present in both recurrent neural network language models (RNNLMs) and latent word language models (LWLMs). The proposed model has a soft class structure based on a latent variable space as well as LWLM, where the latent variable space is modeled using RNNLM. This paper also details the parameter inference method and two kinds of usages for natural language processing tasks. Our experiments show effectiveness of the proposed model on a perplexity evaluation for the Penn Treebank corpus and an automatic speech recognition evaluation for Japanese spontaneous speech tasks.
Keyword (in Japanese) (See Japanese page) 
(in English) latent words recurrent neural network language model / n-gram approximation / Viterbi approximation / / / / /  
Reference Info. IEICE Tech. Rep., vol. 115, no. 184, SP2015-50, pp. 1-6, Aug. 2015.
Paper # SP2015-50 
Date of Issue 2015-08-14 (SP) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
Copyright
and
reproduction
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
Download PDF SP2015-50

Conference Information
Committee SP  
Conference Date 2015-08-21 - 2015-08-21 
Place (in Japanese) (See Japanese page) 
Place (in English) Iwate Prefectural Univ. 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Spoken document processing, etc. 
Paper Information
Registration To SP 
Conference Code 2015-08-SP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Latent Words Recurrent Neural Network Language Models for Automatic Speech Recognition 
Sub Title (in English)  
Keyword(1) latent words recurrent neural network language model  
Keyword(2) n-gram approximation  
Keyword(3) Viterbi approximation  
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1st Author's Name Ryo Masumura  
1st Author's Affiliation Nippon Telegraph and Telephone Corporation (NTT)
2nd Author's Name Taichi Asami  
2nd Author's Affiliation Nippon Telegraph and Telephone Corporation (NTT)
3rd Author's Name Takanobu Oba  
3rd Author's Affiliation Nippon Telegraph and Telephone Corporation (NTT)
4th Author's Name Hirokazu Masataki  
4th Author's Affiliation Nippon Telegraph and Telephone Corporation (NTT)
5th Author's Name Sumitaka Sakauchi  
5th Author's Affiliation Nippon Telegraph and Telephone Corporation (NTT)
6th Author's Name Akinori Ito  
6th Author's Affiliation Tohoku Universicty (Tohoku Universicty)
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Speaker Author-1 
Date Time 2015-08-21 10:00:00 
Presentation Time 25 minutes 
Registration for SP 
Paper # SP2015-50 
Volume (vol) vol.115 
Number (no) no.184 
Page pp.1-6 
#Pages
Date of Issue 2015-08-14 (SP) 


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