We present a survey on multilingual neural machine translation (MNMT), which has gained
a lot of traction in recent years. MNMT has been useful in improving translation quality as a …

This paper describes SentencePiece, a language-independent subword tokenizer and
detokenizer designed for Neural-based text processing, including Neural Machine …

We present a survey covering the state of the art in low-resource machine translation (MT)
research. There are currently around 7,000 languages spoken in the world and almost all …

Subword units are an effective way to alleviate the open vocabulary problems in neural
machine translation (NMT). While sentences are usually converted into unique subword …

Modern neural sequence generation models are built to either generate tokens step-by-step
from scratch or (iteratively) modify a sequence of tokens bounded by a fixed length. In this …

Recent work demonstrates the potential of training one model for multilingual machine
translation. In parallel, denoising pretraining using unlabeled monolingual data as a starting …

We show that margin-based bitext mining in a multilingual sentence space can be applied to
monolingual corpora of billions of sentences. We are using ten snapshots of a curated …

We present Samanantar, the largest publicly available parallel corpora collection for Indic
languages. The collection contains a total of 49.7 million sentence pairs between English …

Neural machine translation (NMT) is a deep learning based approach for machine
translation, which yields the state-of-the-art translation performance in scenarios where …

With the invention of deep learning concepts, Machine Translation (MT) migrated towards
Neural Machine Translation (NMT) architectures, eventually from Statistical Machine …