The first neural machine translation system for the E rzya language (2022)

Abstract: We present the first neural machine translation system for translation between the endangered Erzya language and Russian and the dataset collected by us to train and evaluate it. The BLEU scores are 17 and 19 for translation to Erzya and Russian respectively, and more than half of the translations are rated as acceptable by native speakers. We also adapt our model to translate between Erzya and 10 other languages, but without additional parallel data, the quality on these directions remains low. We release the translation models along with the collected text corpus, a new language identification model, and a multilingual sentence encoder adapted for the Erzya language. These resources will be available at https://github.com/slone-nlp/myv-nmt .

## introduction out of the 7 thousand languages spoken around the world, only a minor fraction is covered by machine translation tools. for example, google translate 1 supports only 133 languages, and a recent model by @xcite supports 202 languages. most other languages are often considered "lowresource", although some of them have millions of native speakers. in the context of machine translation, the resources that are low are, primarily, parallel and monolingual text corpora. in this work, we create a machine translation system for the previously uncovered erzya language with only publicly available resources, a very small budget, and limited human efforts. we hope that it will inspire researchers and language activists to enlarge the coverage of existing nlp resources, and in particular, translation systems. our language of choice is erzya (myv), which is spoken primarily in the republic of mordovia, located in the center of the european part of the russian federation. the language, along with its close relative moksha (mdf), belongs to the mordvinic branch of the uralic language family. these two languages, although not mutually intelligible @xcite , are often referred to under the common name "mordovian". erzya has had a written tradition since the beginning of the 19th century @xcite . its most widely used alphabet is cyrillic, although there is a latin-based alternative alphabet foot_1 . erzya has supposedly 300 thousand speakers foot_2 , and it is one of the three official languages in mordovia. according to the unesco classification, the erzya language has a status of "definitely endangered" @xcite . some researchers @xcite put it between the levels 6b ("threatened") and 7 ("shifting") on the egids scale @xcite , as it is widely used and transmitted between generations in rural communities but is being gradually displaced by russian in urban areas. more details about the use of erzya are given by @xcite , who is also a major current contributor to erzya nlp resources. as far as we know, prior to this work, no neural machine translation (nmt) systems for erzya have been published. to fill this gap, we create and publicly release 4 the following deliverables: ## related work low-resource nlp and, in particular, machine translation, have attracted a lot of attention. among the recent ambitious projects are @xcite and @xcite that aim at creating nmt systems for hundreds of languages and rely heavily on collection of large online corpora and transfer learning. other works, such as @xcite , focus on efficient use of existing vocabularies and morphosyntactic tools to train machine translation systems for very low-resourced languages. as far as we know, there are no published large parallel corpora or nmt systems for erzya. @xcite develop an erzya treebank with a few hundred translations to english and finnish. архангельский (2019) present an erzya web corpus foot_4 along with the way it was collected, but the corpus is available only via the web interface. for other published corpora, the situation is similar. there exists a half-finished rule-based machine translation system between erzya and finnish foot_5 , and a grammar parser for erzya foot_6 . the software package uralicnlp @xcite supports erzya among other languages. there have been a few attempts to transfer machine learning-based nlp resources to erzya from high-resource languages. alnajjar (2021) adapt finnish, english, and russian word embeddings to erzya. @xcite , @xcite and @xcite evaluate the performance of multilingual bert-like models on natural language understanding tasks for new languages, including erzya. none of the works known to us train machine learning-based models that are capable of generating erzya language. ## conclusions and future work in this paper, we present the first nmt system for the endangered erzya language, capable of translating between it and 11 diverse languages, primarily russian. during its development, we have collected about 30k parallel russian-erzya sentences and 300k monolingual erzya sentences, and trained a language identification model and a bert-based sentence encoder that support erzya. all the resources are publicly released. these efforts have occupied about two man-weeks of working time and almost no expenses 19 . we hope that these results will inspire the nlp community to develop resources for other endangered languages. 18 we are not certain whether these errors are due to the low quality of the source text, or to the natural variations within the erzya language. the quality of our system may be improved by collecting more texts in erzya and filtering them better than we did. another promising direction is a more efficient usage of the vocabularies and parsers that are already available for the language, e.g. for generating synthetic training data. finally, we hope to attract more native speakers for creating larger and cleaner train and test datasets. one open research question is that of transfer between languages: whether erzya translation benefits from knowledge of, for example, hungarian or estonian, and whether knowledge of erzya can bring improvements to other languages, such as moksha. in further studies, we hope to shed some light on this direction as well.