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Found 13 papers, 8 papers with code
Findings of the WMT 2021 Shared Task on Large-Scale Multilingual Machine Translation
There were a total of 10 participating teams for the tasks, with a total of 151 intermediate model submissions and 13 final models.
Seamless: Multilingual Expressive and Streaming Speech Translation
In this work, we introduce a family of models that enable end-to-end expressive and multilingual translations in a streaming fashion.
automatic-speech-translation
Multimodal Machine Translation
+2
SeamlessM4T: Massively Multilingual & Multimodal Machine Translation
What does it take to create the Babel Fish, a tool that can help individuals translate speech between any two languages?
Ranked #1 on
Speech-to-Speech Translation
on CVSS
(using extra training data)
Automatic Speech Recognition
Speech-to-Speech Translation
+4
No Language Left Behind: Scaling Human-Centered Machine Translation
Driven by the goal of eradicating language barriers on a global scale, machine translation has solidified itself as a key focus of artificial intelligence research today.
Ranked #1 on
Machine Translation
on IWSLT2017 French-English
(SacreBLEU metric)
How Robust is Neural Machine Translation to Language Imbalance in Multilingual Tokenizer Training?
Since a skewed data distribution is considered to be harmful, a sampling strategy is usually used to balance languages in the corpus.
The FLORES-101 Evaluation Benchmark for Low-Resource and Multilingual Machine Translation
One of the biggest challenges hindering progress in low-resource and multilingual machine translation is the lack of good evaluation benchmarks.
Generating Fact Checking Briefs
Fact checking at scale is difficult -- while the number of active fact checking websites is growing, it remains too small for the needs of the contemporary media ecosystem.
Beyond English-Centric Multilingual Machine Translation
Existing work in translation demonstrated the potential of massively multilingual machine translation by training a single model able to translate between any pair of languages.
Unsupervised Cross-lingual Representation Learning at Scale
We also present a detailed empirical analysis of the key factors that are required to achieve these gains, including the trade-offs between (1) positive transfer and capacity dilution and (2) the performance of high and low resource languages at scale.
CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Data
Pre-training text representations have led to significant improvements in many areas of natural language processing.
Facebook AI's WAT19 Myanmar-English Translation Task Submission
This paper describes Facebook AI's submission to the WAT 2019 Myanmar-English translation task.
Trans-gram, Fast Cross-lingual Word-embeddings
We introduce Trans-gram, a simple and computationally-efficient method to simultaneously learn and align wordembeddings for a variety of languages, using only monolingual data and a smaller set of sentence-aligned data.
