Next Article in Journal
Cross-Domain Text Sentiment Analysis Based on CNN_FT Method
Previous Article in Journal
P2P Botnet Detection Based on Nodes Correlation by the Mahalanobis Distance
Previous Article in Special Issue
Machine Learning Models for Error Detection in Metagenomics and Polyploid Sequencing Data
Article Menu
Issue 5 (May) cover image

Export Article

Open AccessArticle

FastText-Based Intent Detection for Inflected Languages

1
Tilde, Vienības Gatve 75A, LV-1004 Rīga, Latvia
2
Faculty of Computing, University of Latvia, Raiņa blvd. 19, LV-1586 Rīga, Latvia
*
Author to whom correspondence should be addressed.
This paper is an extended version of our paper published in 18th International Conference AIMSA 2018, Varna, Bulgaria, 12–14 September 2018.
Information 2019, 10(5), 161; https://doi.org/10.3390/info10050161
Received: 15 January 2019 / Revised: 12 April 2019 / Accepted: 25 April 2019 / Published: 1 May 2019
(This article belongs to the Special Issue Artificial Intelligence—Methodology, Systems, and Applications)
  |  
PDF [856 KB, uploaded 8 May 2019]
  |  

Abstract

Intent detection is one of the main tasks of a dialogue system. In this paper, we present our intent detection system that is based on fastText word embeddings and a neural network classifier. We find an improvement in fastText sentence vectorization, which, in some cases, shows a significant increase in intent detection accuracy. We evaluate the system on languages commonly spoken in Baltic countries—Estonian, Latvian, Lithuanian, English, and Russian. The results show that our intent detection system provides state-of-the-art results on three previously published datasets, outperforming many popular services. In addition to this, for Latvian, we explore how the accuracy of intent detection is affected if we normalize the text in advance. View Full-Text
Keywords: intent detection; word embeddings; dialogue system intent detection; word embeddings; dialogue system
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Balodis, K.; Deksne, D. FastText-Based Intent Detection for Inflected Languages. Information 2019, 10, 161.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Information EISSN 2078-2489 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top