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Creators/Authors contains: "Pratapa, Adithya"

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  1. ; ; ; ; ; ; (, Evaluating the Morphosyntactic Well-formedness of Generated Texts)
    Text generation systems are ubiquitous in natural language processing applications. However, evaluation of these systems remains a challenge, especially in multilingual settings. In this paper, we propose L’AMBRE – a metric to evaluate the morphosyntactic well-formedness of text using its dependency parse and morphosyntactic rules of the language. We present a way to automatically extract various rules governing morphosyntax directly from dependency treebanks. To tackle the noisy outputs from text generation systems, we propose a simple methodology to train robust parsers. We show the effectiveness of our metric on the task of machine translation through a diachronic study of systems translating into morphologically-rich languages. 
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  2. ; ; ; ; ; ; (, Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP))
    null (Ed.)
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