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Continual Mixed-Language Pre-Training for Extremely Low-Resource Neural Machine Translation ...
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BiToD: A Bilingual Multi-Domain Dataset For Task-Oriented Dialogue Modeling ...
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Adapting High-resource NMT Models to Translate Low-resource Related Languages without Parallel Data ...
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Ko, Wei-Jen; El-Kishky, Ahmed; Renduchintala, Adithya; Chaudhary, Vishrav; Goyal, Naman; Guzmán, Francisco; Fung, Pascale; Koehn, Philipp; Diab, Mona. - : arXiv, 2021
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Abstract:
The scarcity of parallel data is a major obstacle for training high-quality machine translation systems for low-resource languages. Fortunately, some low-resource languages are linguistically related or similar to high-resource languages; these related languages may share many lexical or syntactic structures. In this work, we exploit this linguistic overlap to facilitate translating to and from a low-resource language with only monolingual data, in addition to any parallel data in the related high-resource language. Our method, NMT-Adapt, combines denoising autoencoding, back-translation and adversarial objectives to utilize monolingual data for low-resource adaptation. We experiment on 7 languages from three different language families and show that our technique significantly improves translation into low-resource language compared to other translation baselines. ... : ACL 2021 ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences
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URL: https://arxiv.org/abs/2105.15071 https://dx.doi.org/10.48550/arxiv.2105.15071
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Learning Fast Adaptation on Cross-Accented Speech Recognition ...
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Exploring Fine-tuning Techniques for Pre-trained Cross-lingual Models via Continual Learning ...
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Meta-Transfer Learning for Code-Switched Speech Recognition ...
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On the Importance of Word Order Information in Cross-lingual Sequence Labeling ...
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Attention-Informed Mixed-Language Training for Zero-shot Cross-lingual Task-oriented Dialogue Systems ...
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Zero-shot Cross-lingual Dialogue Systems with Transferable Latent Variables ...
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Towards Universal End-to-End Affect Recognition from Multilingual Speech by ConvNets ...
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Code-Switched Language Models Using Neural Based Synthetic Data from Parallel Sentences ...
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Hierarchical Meta-Embeddings for Code-Switching Named Entity Recognition ...
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GlobalTrait: Personality Alignment of Multilingual Word Embeddings ...
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Learn to Code-Switch: Data Augmentation using Copy Mechanism on Language Modeling ...
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Mem2Seq: Effectively Incorporating Knowledge Bases into End-to-End Task-Oriented Dialog Systems ...
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Bilingual Character Representation for Efficiently Addressing Out-of-Vocabulary Words in Code-Switching Named Entity Recognition ...
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Code-Switching Language Modeling using Syntax-Aware Multi-Task Learning ...
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