The Impact of Indirect Machine Translation on Sentiment Classification
- URL: http://arxiv.org/abs/2008.11257v1
- Date: Tue, 25 Aug 2020 20:30:21 GMT
- Title: The Impact of Indirect Machine Translation on Sentiment Classification
- Authors: Alberto Poncelas, Pintu Lohar, Andy Way, James Hadley
- Abstract summary: We propose employing a machine translation (MT) system to translate customer feedback into another language.
As performing a direct translation is not always possible, we explore the performance of automatic classifiers on sentences that have been translated.
We conduct several experiments to analyse the performance of our proposed sentiment classification system and discuss the advantages and drawbacks of classifying translated sentences.
- Score: 6.719549885077474
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Sentiment classification has been crucial for many natural language
processing (NLP) applications, such as the analysis of movie reviews, tweets,
or customer feedback. A sufficiently large amount of data is required to build
a robust sentiment classification system. However, such resources are not
always available for all domains or for all languages.
In this work, we propose employing a machine translation (MT) system to
translate customer feedback into another language to investigate in which cases
translated sentences can have a positive or negative impact on an automatic
sentiment classifier. Furthermore, as performing a direct translation is not
always possible, we explore the performance of automatic classifiers on
sentences that have been translated using a pivot MT system.
We conduct several experiments using the above approaches to analyse the
performance of our proposed sentiment classification system and discuss the
advantages and drawbacks of classifying translated sentences.
Related papers
Err
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.