most citedA Survey of Methods to Leverage Monolingual Data in Low-resource Neural Machine Translation

12 citations · 26 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CL20213 cited

Evaluation of Morphological Embeddings for English and Russian Languages

Vitaly Romanov, Albina Khusainova

This paper evaluates morphology-based embeddings for English and Russian languages. Despite the interest and introduction of several morphology-based word embedding models in the p…

cs.CL20213 cited

Evaluation of Morphological Embeddings for the Russian Language

Vitaly Romanov, Albina Khusainova

A number of morphology-based word embedding models were introduced in recent years. However, their evaluation was mostly limited to English, which is known to be a morphologically…

cs.CL20211 cited

Hierarchical Transformer for Multilingual Machine Translation

Albina Khusainova, Adil Khan, Adín Ramírez Rivera +1

The choice of parameter sharing strategy in multilingual machine translation models determines how optimally parameter space is used and hence, directly influences ultimate transla…

cs.CL201912 cited

A Survey of Methods to Leverage Monolingual Data in Low-resource Neural Machine Translation

Ilshat Gibadullin, Aidar Valeev, Albina Khusainova +1

Neural machine translation has become the state-of-the-art for language pairs with large parallel corpora. However, the quality of machine translation for low-resource languages le…

cs.CL20197 cited

Application of Low-resource Machine Translation Techniques to Russian-Tatar Language Pair

Aidar Valeev, Ilshat Gibadullin, Albina Khusainova +1

Neural machine translation is the current state-of-the-art in machine translation. Although it is successful in a resource-rich setting, its applicability for low-resource language…

cs.CL2019

SART - Similarity, Analogies, and Relatedness for Tatar Language: New Benchmark Datasets for Word Embeddings Evaluation

Albina Khusainova, Adil Khan, Adín Ramírez Rivera

There is a huge imbalance between languages currently spoken and corresponding resources to study them. Most of the attention naturally goes to the "big" languages: those which hav…