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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

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • 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

  • 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