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XTREME-S: Evaluating Cross-lingual Speech Representations ...
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One Country, 700+ Languages: NLP Challenges for Underrepresented Languages and Dialects in Indonesia ...
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Expanding Pretrained Models to Thousands More Languages via Lexicon-based Adaptation ...
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Abstract:
The performance of multilingual pretrained models is highly dependent on the availability of monolingual or parallel text present in a target language. Thus, the majority of the world's languages cannot benefit from recent progress in NLP as they have no or limited textual data. To expand possibilities of using NLP technology in these under-represented languages, we systematically study strategies that relax the reliance on conventional language resources through the use of bilingual lexicons, an alternative resource with much better language coverage. We analyze different strategies to synthesize textual or labeled data using lexicons, and how this data can be combined with monolingual or parallel text when available. For 19 under-represented languages across 3 tasks, our methods lead to consistent improvements of up to 5 and 15 points with and without extra monolingual text respectively. Overall, our study highlights how NLP methods can be adapted to thousands more languages that are under-served by ... : ACL 2022 ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences
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URL: https://arxiv.org/abs/2203.09435 https://dx.doi.org/10.48550/arxiv.2203.09435
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MasakhaNER: Named entity recognition for African languages
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In: EISSN: 2307-387X ; Transactions of the Association for Computational Linguistics ; https://hal.inria.fr/hal-03350962 ; Transactions of the Association for Computational Linguistics, The MIT Press, 2021, ⟨10.1162/tacl⟩ (2021)
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Charformer: Fast Character Transformers via Gradient-based Subword Tokenization ...
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XTREME-R: Towards More Challenging and Nuanced Multilingual Evaluation ...
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Efficient Test Time Adapter Ensembling for Low-resource Language Varieties ...
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XTREME-R: Towards More Challenging and Nuanced Multilingual Evaluation ...
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A Call for More Rigor in Unsupervised Cross-lingual Learning ...
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Rethinking embedding coupling in pre-trained language models ...
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MAD-X: An Adapter-Based Framework for Multi-Task Cross-Lingual Transfer ...
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How Good is Your Tokenizer? On the Monolingual Performance of Multilingual Language Models ...
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UNKs Everywhere: Adapting Multilingual Language Models to New Scripts ...
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MAD-X: An Adapter-Based Framework for Multi-Task Cross-Lingual Transfer ...
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Morphologically Aware Word-Level Translation
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In: Proceedings of the 28th International Conference on Computational Linguistics (2020)
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XTREME: A Massively Multilingual Multi-task Benchmark for Evaluating Cross-lingual Generalization ...
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