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Found 13 papers, 1 papers with code
Developing Machine Translation Engines for Multilingual Participatory Spaces
It is often a challenging task to build Machine Translation (MT) engines for a specific domain due to the lack of parallel data in that area.
TransCasm: A Bilingual Corpus of Sarcastic Tweets
Sarcasm is extensively used in User Generated Content (UGC) in order to express one’s discontent, especially through blogs, forums, or social media such as Twitter.
Effective Bitext Extraction From Comparable Corpora Using a Combination of Three Different Approaches
Parallel sentences extracted from comparable corpora can be useful to supplement parallel corpora when training machine translation (MT) systems.
Building Machine Translation System for Software Product Descriptions Using Domain-specific Sub-corpora Extraction
Moreover, we developed a first-ever test parallel data set of product descriptions.
The Impact of Indirect Machine Translation on Sentiment Classification
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.
Building English-to-Serbian Machine Translation System for IMDb Movie Reviews
This paper reports the results of the first experiment dealing with the challenges of building a machine translation system for user-generated content involving a complex South Slavic language.
ADAPT at IJCNLP-2017 Task 4: A Multinomial Naive Bayes Classification Approach for Customer Feedback Analysis task
In this paper, we analyse the real world samples of customer feedback from Microsoft Office customers in four languages, i. e., English, French, Spanish and Japanese and conclude a five-plus-one-classes categorisation (comment, request, bug, complaint, meaningless and undetermined) for meaning classification.
MultiNews: A Web collection of an Aligned Multimodal and Multilingual Corpus
Integrating Natural Language Processing (NLP) and computer vision is a promising effort.
Content-Based Image Retrieval
Multimodal Machine Translation
Using Images to Improve Machine-Translating E-Commerce Product Listings.
We evaluate our models quantitatively using BLEU and TER and find that (i) additional synthetic data has a general positive impact on text-only and multi-modal NMT models, and that (ii) using a multi-modal NMT model for re-ranking n-best lists improves TER significantly across different n-best list sizes.
