An Exploration of Data Augmentation Techniques for Improving English to Tigrinya Translation

• URL: http://arxiv.org/abs/2103.16789v1
• Date: Wed, 31 Mar 2021 03:31:09 GMT
• Title: An Exploration of Data Augmentation Techniques for Improving English to Tigrinya Translation
• Authors: Lidia Kidane, Sachin Kumar, Yulia Tsvetkov
• Abstract summary: An effective method of generating auxiliary data is back-translation of target language sentences. We present a case study of Tigrinya where we investigate several back-translation methods to generate synthetic source sentences.
• Score: 21.636157115922693
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: It has been shown that the performance of neural machine translation (NMT) drops starkly in low-resource conditions, often requiring large amounts of auxiliary data to achieve competitive results. An effective method of generating auxiliary data is back-translation of target language sentences. In this work, we present a case study of Tigrinya where we investigate several back-translation methods to generate synthetic source sentences. We find that in low-resource conditions, back-translation by pivoting through a higher-resource language related to the target language proves most effective resulting in substantial improvements over baselines.

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