NMTScore: A Multilingual Analysis of Translation-based Text Similarity Measures

• URL: http://arxiv.org/abs/2204.13692v1
• Date: Thu, 28 Apr 2022 17:57:17 GMT
• Title: NMTScore: A Multilingual Analysis of Translation-based Text Similarity Measures
• Authors: Jannis Vamvas and Rico Sennrich
• Abstract summary: We analyze translation-based similarity measures in the common framework of multilingual NMT. Compared to baselines such as sentence embeddings, translation-based measures prove competitive in paraphrase identification. Measures show a relatively high correlation to human judgments.
• Score: 42.46681912294797
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Being able to rank the similarity of short text segments is an interesting bonus feature of neural machine translation. Translation-based similarity measures include direct and pivot translation probability, as well as translation cross-likelihood, which has not been studied so far. We analyze these measures in the common framework of multilingual NMT, releasing the NMTScore library (available at https://github.com/ZurichNLP/nmtscore). Compared to baselines such as sentence embeddings, translation-based measures prove competitive in paraphrase identification and are more robust against adversarial or multilingual input, especially if proper normalization is applied. When used for reference-based evaluation of data-to-text generation in 2 tasks and 17 languages, translation-based measures show a relatively high correlation to human judgments.

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