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Rule-based Morphological Inflection Improves Neural Terminology Translation ...
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Translating Headers of Tabular Data: A Pilot Study of Schema Translation ...
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Abstract:
Anthology paper link: https://aclanthology.org/2021.emnlp-main.5/ Abstract: Schema translation is the task of automatically translating headers of tabular data from one language to another. High-quality schema translation plays an important role in cross-lingual table searching, understanding and analysis. Despite its importance, schema translation is not well studied in the community, and state-of-the-art neural machine translation models cannot work well on this task because of two intrinsic differences between plain text and tabular data: morphological difference and context difference. To facilitate the research study, we construct the first parallel dataset for schema translation, which consists of 3,158 tables with 11,979 headers written in 6 different languages, including English, Chinese, French, German, Spanish, and Japanese. Also, we propose the first schema translation model called CAST, which is a header-to-header neural machine translation model augmented with schema context. Specifically, we ...
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Keyword:
Computational Linguistics; Machine Learning; Machine Learning and Data Mining; Machine translation; Natural Language Processing
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URL: https://underline.io/lecture/37570-translating-headers-of-tabular-data-a-pilot-study-of-schema-translation https://dx.doi.org/10.48448/e3w6-dn36
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An Information-Theoretic Characterization of Morphological Fusion ...
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Analyzing the Surprising Variability in Word Embedding Stability Across Languages ...
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Neural Machine Translation with Heterogeneous Topic Knowledge Embeddings ...
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STaCK: Sentence Ordering with Temporal Commonsense Knowledge ...
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Wikily Supervised Neural Translation Tailored to Cross-Lingual Tasks ...
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Cross-Attention is All You Need: Adapting Pretrained Transformers for Machine Translation ...
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Rethinking Data Augmentation for Low-Resource Neural Machine Translation: A Multi-Task Learning Approach ...
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Sequence Length is a Domain: Length-based Overfitting in Transformer Models ...
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Speechformer: Reducing Information Loss in Direct Speech Translation ...
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Data and Parameter Scaling Laws for Neural Machine Translation ...
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A Simple Geometric Method for Cross-Lingual Linguistic Transformations with Pre-trained Autoencoders ...
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Universal Simultaneous Machine Translation with Mixture-of-Experts Wait-k Policy ...
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Learning to Rewrite for Non-Autoregressive Neural Machine Translation ...
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Towards Making the Most of Dialogue Characteristics for Neural Chat Translation ...
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Improving the Quality Trade-Off for Neural Machine Translation Multi-Domain Adaptation ...
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