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The effect of domain and diacritics in Yorùbá-English neural machine translation
In: 18th Biennial Machine Translation Summit ; https://hal.inria.fr/hal-03350967 ; 18th Biennial Machine Translation Summit, Aug 2021, Orlando, United States (2021)
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The Effect of Domain and Diacritics in Yorùbá-English Neural Machine Translation ...
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Emoji-Based Transfer Learning for Sentiment Tasks ...
Abstract: Sentiment tasks such as hate speech detection and sentiment analysis, especially when performed on languages other than English, are often low-resource. In this study, we exploit the emotional information encoded in emojis to enhance the performance on a variety of sentiment tasks. This is done using a transfer learning approach, where the parameters learned by an emoji-based source task are transferred to a sentiment target task. We analyse the efficacy of the transfer under three conditions, i.e. i) the emoji content and ii) label distribution of the target task as well as iii) the difference between monolingually and multilingually learned source tasks. We find i.a. that the transfer is most beneficial if the target task is balanced with high emoji content. Monolingually learned source tasks have the benefit of taking into account the culturally specific use of emojis and gain up to F1 +0.280 over the baseline. ... : 6 pages, 2 figures, accepted at EACL-SRW 2021 ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences
URL: https://arxiv.org/abs/2102.06423
https://dx.doi.org/10.48550/arxiv.2102.06423
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EdinSaar@WMT21: North-Germanic Low-Resource Multilingual NMT ...
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5
Integrating Unsupervised Data Generation into Self-Supervised Neural Machine Translation for Low-Resource Languages ...
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6
Modeling Profanity and Hate Speech in Social Media with Semantic Subspaces ...
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