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Found 15 papers, 0 papers with code
Machine Translation in the Covid domain: an English-Irish case study for LoResMT 2021
Translation models for the specific domain of translating Covid data from English to Irish were developed for the LoResMT 2021 shared task.
Enabling Deep Learning for All-in EDGE paradigm
Moreover, it is suitable from the data requirements perspective in the edge paradigm because the proliferation of edge devices has resulted in an explosion in the volume of generated and collected data.
Splitfed learning without client-side synchronization: Analyzing client-side split network portion size to overall performance
Federated Learning (FL), Split Learning (SL), and SplitFed Learning (SFL) are three recent developments in distributed machine learning that are gaining attention due to their ability to preserve the privacy of raw data.
Hierarchical Deep Learning for Arabic Dialect Identification
In this paper, we present two approaches for Arabic Fine-Grained Dialect Identification.
EPITA-ADAPT at SemEval-2019 Task 3: Detecting emotions in textual conversations using deep learning models combination
Our proposed system is based on the combination of different deep neural networks techniques.
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
+1
Identifying Effective Translations for Cross-lingual Arabic-to-English User-generated Speech Search
Cross Language Information Retrieval (CLIR) systems are a valuable tool to enable speakers of one language to search for content of interest expressed in a different language.
Integrating Optical Character Recognition and Machine Translation of Historical Documents
Such documents must be passed through a process of Optical Character Recognition (OCR) to render the text suitable for MT.
Using SMT for OCR Error Correction of Historical Texts
A trend to digitize historical paper-based archives has emerged in recent years, with the advent of digital optical scanners.
