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Found 23 papers, 1 papers with code
N-gram and Neural Models for Uralic Language Identification: NRC at VarDial 2021
We describe the systems developed by the National Research Council Canada for the Uralic language identification shared task at the 2021 VarDial evaluation campaign.
Challenges in Neural Language Identification: NRC at VarDial 2020
We describe the systems developed by the National Research Council Canada for the Uralic language identification shared task at the 2020 VarDial evaluation campaign.
Transfer Learning Improves French Cross-Domain Dialect Identification: NRC @ VarDial 2022
We describe the systems developed by the National Research Council Canada for the French Cross-Domain Dialect Identification shared task at the 2022 VarDial evaluation campaign.
Refining an Almost Clean Translation Memory Helps Machine Translation
While recent studies have been dedicated to cleaning very noisy parallel corpora to improve Machine Translation training, we focus in this work on filtering a large and mostly clean Translation Memory.
Improving Cuneiform Language Identification with BERT
We describe the systems developed by the National Research Council Canada for the Cuneiform Language Identification (CLI) shared task at the 2019 VarDial evaluation campaign.
Accurate semantic textual similarity for cleaning noisy parallel corpora using semantic machine translation evaluation metric: The NRC supervised submissions to the Parallel Corpus Filtering task
We present our semantic textual similarity approach in filtering a noisy web crawled parallel corpus using YiSi{---}a novel semantic machine translation evaluation metric.
Measuring sentence parallelism using Mahalanobis distances: The NRC unsupervised submissions to the WMT18 Parallel Corpus Filtering shared task
The WMT18 shared task on parallel corpus filtering (Koehn et al., 2018b) challenged teams to score sentence pairs from a large high-recall, low-precision web-scraped parallel corpus (Koehn et al., 2018a).
Real-time Change Point Detection using On-line Topic Models
Detecting changes within an unfolding event in real time from news articles or social media enables to react promptly to serious issues in public safety, public health or natural disasters.
Exploring Optimal Voting in Native Language Identification
We mainly explored the use of voting, and various ways to optimize the choice and number of voting systems.
Detecting Changes in Twitter Streams using Temporal Clusters of Hashtags
Detecting events from social media data has important applications in public security, political issues, and public health.
Extracting Discriminative Keyphrases with Learned Semantic Hierarchies
We show that such knowledge can be used to construct better discriminative keyphrase extraction systems that do not assume a static, fixed set of keyphrases for a document.
Advances in Ngram-based Discrimination of Similar Languages
We describe the systems entered by the National Research Council in the 2016 shared task on discriminating similar languages.
Discriminating Similar Languages: Evaluations and Explorations
We present an analysis of the performance of machine learning classifiers on discriminating between similar languages and language varieties.
Learning from Multiple Partially Observed Views - an Application to Multilingual Text Categorization
We assume the existence of view generating functions which may complete the missing views in an approximate way.
