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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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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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Abstract:
Despite the surging demands for multilingual task-oriented dialog systems (e.g., Alexa, Google Home), there has been less research done in multilingual or cross-lingual scenarios. Hence, we propose a zero-shot adaptation of task-oriented dialogue system to low-resource languages. To tackle this challenge, we first use a set of very few parallel word pairs to refine the aligned cross-lingual word-level representations. We then employ a latent variable model to cope with the variance of similar sentences across different languages, which is induced by imperfect cross-lingual alignments and inherent differences in languages. Finally, the experimental results show that even though we utilize much less external resources, our model achieves better adaptation performance for natural language understanding task (i.e., the intent detection and slot filling) compared to the current state-of-the-art model in the zero-shot scenario. ... : Accepted in EMNLP 2019 ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences; Machine Learning cs.LG
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URL: https://dx.doi.org/10.48550/arxiv.1911.04081 https://arxiv.org/abs/1911.04081
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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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