On the Effects of Using word2vec Representations in Neural Networks for Dialogue Act Recognition
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F18%3A43951550" target="_blank" >RIV/49777513:23520/18:43951550 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1016/j.csl.2017.07.009" target="_blank" >http://dx.doi.org/10.1016/j.csl.2017.07.009</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.csl.2017.07.009" target="_blank" >10.1016/j.csl.2017.07.009</a>
Alternative languages
Result language
angličtina
Original language name
On the Effects of Using word2vec Representations in Neural Networks for Dialogue Act Recognition
Original language description
Dialogue act recognition is an important component of a large number of natural language processing pipelines. Many research works have been carried out in this area, but relatively few investigate deep neural networks and word embeddings. We propose in this work a new deep neural network that explores recurrent models to capture word sequences within sentences, and further study the impact of pretrained word embeddings. We validate this model on three languages: English, French and Czech. The performance of the proposed approach is consistent across these languages and it is comparable to the state-of-the-art results in English. However, and this is more surprising, we also found that standard word2vec embeddings do not seem to bring valuable information for this task and the proposed model.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
<a href="/en/project/LO1506" target="_blank" >LO1506: Sustainability support of the centre NTIS - New Technologies for the Information Society</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Computer Speech and Language
ISSN
0885-2308
e-ISSN
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Volume of the periodical
47
Issue of the periodical within the volume
JAN 2018
Country of publishing house
GB - UNITED KINGDOM
Number of pages
19
Pages from-to
175-193
UT code for WoS article
000411903700011
EID of the result in the Scopus database
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