Evaluation of NMT-Assisted Grammar Transfer for a Multi-Language Configurable Data-to-Text System

• URL: http://arxiv.org/abs/2501.16135v1
• Date: Mon, 27 Jan 2025 15:25:26 GMT
• Title: Evaluation of NMT-Assisted Grammar Transfer for a Multi-Language Configurable Data-to-Text System
• Authors: Andreas Madsack, Johanna Heininger, Adela Schneider, Ching-Yi Chen, Christian Eckard, Robert Weißgraeber,
• Abstract summary: One approach for multilingual data-to-text generation is to translate grammatical configurations upfront from the source language into each target language. In this paper, we describe a rule-based NLG implementation where the configuration is translated by Neural Machine Translation (NMT) combined with a one-time human review. Our evaluation on the SportSett:Basketball dataset shows that our NLG system performs well, underlining its grammatical correctness in translation tasks.
• Score: 0.04947896909360667
• License:
• Abstract: One approach for multilingual data-to-text generation is to translate grammatical configurations upfront from the source language into each target language. These configurations are then used by a surface realizer and in document planning stages to generate output. In this paper, we describe a rule-based NLG implementation of this approach where the configuration is translated by Neural Machine Translation (NMT) combined with a one-time human review, and introduce a cross-language grammar dependency model to create a multilingual NLG system that generates text from the source data, scaling the generation phase without a human in the loop. Additionally, we introduce a method for human post-editing evaluation on the automatically translated text. Our evaluation on the SportSett:Basketball dataset shows that our NLG system performs well, underlining its grammatical correctness in translation tasks.

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