A claimed 2B-parameter multi-task translation model for 36 Indian languages, built from pivoted and synthetic corpora, evaluated without baselines and with inconsistent reported numbers.
PHINC: A Parallel Hinglish Social Media Code-Mixed Corpus for Machine Translation
1 Pith paper cite this work. Polarity classification is still indexing.
abstract
Code-mixing is the phenomenon of using more than one language in a sentence. It is a very frequently observed pattern of communication on social media platforms. Flexibility to use multiple languages in one text message might help to communicate efficiently with the target audience. But, it adds to the challenge of processing and understanding natural language to a much larger extent. This paper presents a parallel corpus of the 13,738 code-mixed English-Hindi sentences and their corresponding translation in English. The translations of sentences are done manually by the annotators. We are releasing the parallel corpus to facilitate future research opportunities in code-mixed machine translation. The annotated corpus is available at https://doi.org/10.5281/zenodo.3605597.
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BhashaVerse : Translation Ecosystem for Indian Subcontinent Languages
A claimed 2B-parameter multi-task translation model for 36 Indian languages, built from pivoted and synthetic corpora, evaluated without baselines and with inconsistent reported numbers.