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Tools for supporting language learning for Sakha
Revita is a freely available online language learning platform for learners beyond the beginner level.
Semi-automatically Annotated Learner Corpus for Russian
We present ReLCo— the Revita Learner Corpus—a new semi-automatically annotated learner corpus for Russian.
Projecting named entity recognizers without annotated or parallel corpora
Named entity recognition (NER) is a well-researched task in the field of NLP, which typically requires large annotated corpora for training usable models.
Assessing Grammatical Correctness in Language Learning
We approach the problem with the methods for grammatical error detection (GED), since we hypothesize that models for detecting grammatical mistakes can assess the correctness of potential alternative answers in a learning setting.
Applying Gamification Incentives in the Revita Language-learning System
Our goal is to keep the learner engaged in long practice sessions over many months—rather than for the short-term.
Slav-NER: the 3rd Cross-lingual Challenge on Recognition, Normalization, Classification, and Linking of Named Entities across Slavic Languages
Seven teams covered all six languages, and five teams participated in the cross-lingual entity linking task.
Cross-lingual Named Entity Corpus for Slavic Languages
The corpus consists of 5 017 documents on seven topics.
Effects of sub-word segmentation on performance of transformer language models
Lastly, we show 4. that LMs of smaller size using morphological segmentation can perform comparably to models of larger size trained with BPE -- both in terms of (1) perplexity and (3) scores on downstream tasks.
Linguistic Constructs as the Representation of the Domain Model in an Intelligent Language Tutoring System
This paper presents the development of an AI-based language learning platform Revita.
Question Answering and Question Generation for Finnish
We present the first neural QA and QG models that work with Finnish.
Neural disambiguation of lemma and part of speech in morphologically rich languages
We consider the problem of disambiguating the lemma and part of speech of ambiguous words in morphologically rich languages.
Toward a Paradigm Shift in Collection of Learner Corpora
We present the first version of the longitudinal Revita Learner Corpus (ReLCo), for Russian.
Modeling language learning using specialized Elo rating
This application of Elo provides ratings for learners and concepts which correlate well with subjective proficiency levels of the learners and difficulty levels of the concepts.
The Second Cross-Lingual Challenge on Recognition, Normalization, Classification, and Linking of Named Entities across Slavic Languages
The task is recognizing mentions of named entities in Web documents, their normalization, and cross-lingual linking.
Comparison of Representations of Named Entities for Document Classification
We explore representations for multi-word names in text classification tasks, on Reuters (RCV1) topic and sector classification.
Benchmarks and models for entity-oriented polarity detection
We address the problem of determining entity-oriented polarity in business news.
HCS at SemEval-2017 Task 5: Polarity detection in business news using convolutional neural networks
Task 5 of SemEval-2017 involves fine-grained sentiment analysis on financial microblogs and news.
The First Cross-Lingual Challenge on Recognition, Normalization, and Matching of Named Entities in Slavic Languages
The reported evaluation figures reflect the relatively higher level of complexity of named entity-related tasks in the context of processing texts in Slavic languages.
Grouping business news stories based on salience of named entities
In news aggregation systems focused on broad news domains, certain stories may appear in multiple articles.
A Novel Evaluation Method for Morphological Segmentation
Unsupervised learning of morphological segmentation of words in a language, based only on a large corpus of words, is a challenging task.
