Papers by Zhaoran Ma

    1 papers
    Planning and Generating Natural and Diverse Disfluent Texts as Augmentation for Disfluency Detection (2020.emnlp-main)

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    Challenge: Existing approaches to disfluency detection heavily depend on labeled data.
    Approach: They propose a Planner-Generator based disfluency generation model that generates natural disfluent texts as augmented data.
    Outcome: The proposed model outperforms baselines and leads to state-of-the-art performance on Switchboard corpus.

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