Multitask Finetuning for Improving Neural Machine Translation in Indian Languages
Transformer based language models have led to impressive results across all domains in Natural Language Processing. Pretraining these models on language modeling tasks and finetuning them on downstream tasks such as Text Classification, Question Answering and Neural Machine Translation has consistently shown exemplary results. In this work, we propose a Multitask Finetuning methodology which combines the Bilingual Machine Translation task with an auxiliary Causal Language Modeling task to improve performance on the former task on Indian Languages. We conduct an empirical study on three language pairs, Marathi-Hindi, Marathi-English and Hindi-English, where we compare the multitask finetuning approach to the standard finetuning approach, for which we use the mBART50 model. Our study indicates that the multitask finetuning method could be a better technique than standard finetuning, and could improve Bilingual Machine Translation across language pairs.
Code (0)
등록된 구현이 없습니다.
Tasks
Causal Language ModelingLanguage ModelingLanguage ModellingMachine TranslationQuestion Answeringtext-classificationText ClassificationTranslationSimilar Papers 제목 키워드 기반
Translation Of Telugu-Marathi and Vice-Versa using Rule Based Machine Translation
In todays digital world automated Machine Translation of one language to another has covered a long way to achieve different kinds of success stories. Whereas Babel Fish supports a good number of foreign languages and on…
Machine TranslationTranslationShata-Anuvadak: Tackling Multiway Translation of Indian Languages
We present a compendium of 110 Statistical Machine Translation systems built from parallel corpora of 11 Indian languages belonging to both Indo-Aryan and Dravidian families. We analyze the relationship between translati…
Machine TranslationTranslationTransliterationMachine Translation in Indian Languages: Challenges and Resolution
English to Indian language machine translation poses the challenge of structural and morphological divergence. This paper describes English to Indian language statistical machine translation using pre-ordering and suffix…
Machine TranslationTranslationStatistical Machine Translation for Indian Languages: Mission Hindi 2
This paper presents Centre for Development of Advanced Computing Mumbai's (CDACM) submission to NLP Tools Contest on Statistical Machine Translation in Indian Languages (ILSMT) 2015 (collocated with ICON 2015). The aim o…
Machine TranslationTranslationStatistical Machine Translation for Indian Languages: Mission Hindi
This paper discusses Centre for Development of Advanced Computing Mumbai's (CDACM) submission to the NLP Tools Contest on Statistical Machine Translation in Indian Languages (ILSMT) 2014 (collocated with ICON 2014). The …
Machine TranslationTranslation