Combining Textual and Speech Features in the NLI Task Using State-of-the-Art Machine Learning Techniques
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F17%3A43932939" target="_blank" >RIV/49777513:23520/17:43932939 - isvavai.cz</a>
Result on the web
<a href="http://www.aclweb.org/anthology/W/W17/W17-5021.pdf" target="_blank" >http://www.aclweb.org/anthology/W/W17/W17-5021.pdf</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.18653/v1/W17-5021" target="_blank" >10.18653/v1/W17-5021</a>
Alternative languages
Result language
angličtina
Original language name
Combining Textual and Speech Features in the NLI Task Using State-of-the-Art Machine Learning Techniques
Original language description
We summarize the involvement of our CEMI team in the Native Language Identification shared task, NLI Shared Task~2017, which deals with both textual and speech input data. We submitted the results achieved by using three different system architectures; each of them combines multiple supervised learning models trained on various feature sets. As expected, better results are achieved with the systems that use both the textual data and the spoken responses. Combining the input data of two different modalities led to a rather dramatic improvement in classification performance. Our best performing method is based on a set of feed-forward neural networks whose hidden-layer outputs are combined together using a softmax layer. We achieved a macro-averaged F1 score of 0.9257 on the evaluation (unseen) test set and our team placed first in the main task together with other three teams.
Czech name
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Czech description
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Classification
Type
O - Miscellaneous
CEP classification
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OECD FORD branch
20205 - Automation and control systems
Result continuities
Project
<a href="/en/project/GBP103%2F12%2FG084" target="_blank" >GBP103/12/G084: Center for Large Scale Multi-modal Data Interpretation</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů