Combining Topic Information and Structure Information in a Dynamic Language Model

2009 ◽  
pp. 218-225 ◽  
Author(s):  
Pascal Wiggers ◽  
Leon Rothkrantz
Keyword(s):  
Language Model ◽  
Structure Information ◽  
Dynamic Language

scholarly journals Bert-Enhanced Text Graph Neural Network for Classification

Entropy ◽  
2021 ◽  
Vol 23 (11) ◽  
pp. 1536
Author(s):  
Yiping Yang ◽  
Xiaohui Cui
Keyword(s):  
Neural Network ◽  
Semantic Information ◽  
Structural Information ◽  
Text Processing ◽  
Language Model ◽  
Research Direction ◽  
Semantic Features ◽  
Structure Information ◽  
Single Text ◽  
Graph Neural Networks

Text classification is a fundamental research direction, aims to assign tags to text units. Recently, graph neural networks (GNN) have exhibited some excellent properties in textual information processing. Furthermore, the pre-trained language model also realized promising effects in many tasks. However, many text processing methods cannot model a single text unit’s structure or ignore the semantic features. To solve these problems and comprehensively utilize the text’s structure information and semantic information, we propose a Bert-Enhanced text Graph Neural Network model (BEGNN). For each text, we construct a text graph separately according to the co-occurrence relationship of words and use GNN to extract text features. Moreover, we employ Bert to extract semantic features. The former part can take into account the structural information, and the latter can focus on modeling the semantic information. Finally, we interact and aggregate these two features of different granularity to get a more effective representation. Experiments on standard datasets demonstrate the effectiveness of BEGNN.

Dynamic language model adaptation using keyword category classification

2010 ◽  
Author(s):  
Hitoshi Yamamoto ◽  
Ken Hanazawa ◽  
Kiyokazu Miki ◽  
Koichi Shinoda
Keyword(s):  
Language Model ◽  
Model Adaptation ◽  
Language Model Adaptation ◽  
Dynamic Language

Topic identification techniques applied to dynamic language model adaptation for automatic speech recognition

2015 ◽  
Vol 42 (1) ◽  
pp. 101-112 ◽  
Author(s):  
J.D. Echeverry-Correa ◽  
J. Ferreiros-López ◽  
A. Coucheiro-Limeres ◽  
R. Córdoba ◽  
J.M. Montero
Keyword(s):  
Speech Recognition ◽  
Automatic Speech Recognition ◽  
Language Model ◽  
Model Adaptation ◽  
Topic Identification ◽  
Language Model Adaptation ◽  
Dynamic Language ◽  
Identification Techniques

scholarly journals A dynamic language model based on individual word domains

2000 ◽  
Author(s):  
E. I. Sicilia-Garcia ◽  
Ji Ming ◽  
F. J. Smith
Keyword(s):  
Language Model ◽  
Model Based ◽  
Individual Word ◽  
Dynamic Language

scholarly journals Dynamic language model adaptation using presentation slides for lecture speech recognition

2007 ◽  
Author(s):  
Hiroki Yamazaki ◽  
Koji Iwano ◽  
Koichi Shinoda ◽  
Sadaoki Furui ◽  
Haruo Yokota
Keyword(s):  
Speech Recognition ◽  
Language Model ◽  
Model Adaptation ◽  
Language Model Adaptation ◽  
Dynamic Language

Dynamic language model for speech recognition

1995 ◽  
Vol 98 (2) ◽  
pp. 689-689
Author(s):  
Robert D. Strong
Keyword(s):  
Speech Recognition ◽  
Language Model ◽  
Dynamic Language

A dynamic language model for speech recognition

1991 ◽  
Author(s):  
F. Jelinek ◽  
B. Merialdo ◽  
S. Roukos ◽  
M. Strauss
Keyword(s):  
Speech Recognition ◽  
Language Model ◽  
Dynamic Language
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