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AUTOLEX: An Automatic Framework for Linguistic Exploration ...
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SD-QA: Spoken Dialectal Question Answering for the Real World ...
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Phoneme Recognition through Fine Tuning of Phonetic Representations: a Case Study on Luhya Language Varieties ...
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Machine Translation into Low-resource Language Varieties ...
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Code to Comment Translation: A Comparative Study on Model Effectiveness & Errors ...
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Systematic Inequalities in Language Technology Performance across the World's Languages ...
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Multilingual Code-Switching for Zero-Shot Cross-Lingual Intent Prediction and Slot Filling ...
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Abstract:
Predicting user intent and detecting the corresponding slots from text are two key problems in Natural Language Understanding (NLU). In the context of zero-shot learning, this task is typically approached by either using representations from pre-trained multilingual transformers such as mBERT, or by machine translating the source data into the known target language and then fine-tuning. Our work focuses on a particular scenario where the target language is unknown during training. To this goal, we propose a novel method to augment the monolingual source data using multilingual code-switching via random translations to enhance a transformer's language neutrality when fine-tuning it for a downstream task. This method also helps discover novel insights on how code-switching with different language families around the world impact the performance on the target language. Experiments on the benchmark dataset of MultiATIS++ yielded an average improvement of +4.2% in accuracy for intent task and +1.8% in F1 for slot ...
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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://arxiv.org/abs/2103.07792 https://dx.doi.org/10.48550/arxiv.2103.07792
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Investigating Post-pretraining Representation Alignment for Cross-Lingual Question Answering ...
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Towards More Equitable Question Answering Systems: How Much More Data Do You Need? ...
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Cross-Lingual Text Classification of Transliterated Hindi and Malayalam ...
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Evaluating the Morphosyntactic Well-formedness of Generated Texts ...
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Lexically Aware Semi-Supervised Learning for OCR Post-Correction ...
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When is Wall a Pared and when a Muro? -- Extracting Rules Governing Lexical Selection ...
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Towards Minimal Supervision BERT-based Grammar Error Correction ...
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SIGMORPHON 2020 Shared Task 0: Typologically Diverse Morphological Inflection ...
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It's not a Non-Issue: Negation as a Source of Error in Machine Translation ...
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Automatic Extraction of Rules Governing Morphological Agreement ...
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A Summary of the First Workshop on Language Technology for Language Documentation and Revitalization ...
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Universal Phone Recognition with a Multilingual Allophone System ...
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