Papers with conversational corpora

3 papers
Building and curating conversational corpora for diversity-aware language science and technology (2022.lrec-1)

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Challenge: Language resources that capture language use in its natural habitat of social interaction are rare despite the obvious merits of studying the very environment where we all learn and use it everyday.
Approach: They propose to build an analysis pipeline and best practice guidelines for building and curating corpora of everyday conversation in diverse languages.
Outcome: The proposed pipeline can be used to collect and curate conversational corpora in 67 languages and varieties from 28 phyla.
From text to talk: Harnessing conversational corpora for humane and diversity-aware language technology (2022.acl-long)

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Challenge: Informal social interaction is the primordial home of human language.
Approach: They show that linguistically diverse conversational corpora can provide empirical foundations for flexible, localizable language technologies of the future.
Outcome: The results suggest that even relatively small corpora can support robust generalizations about key aspects of interactional infrastructure.
Revisit Few-shot Intent Classification with PLMs: Direct Fine-tuning vs. Continual Pre-training (2023.findings-acl)

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Challenge: Recent progress in intent detection relies on deep models and datasets with well-crafted annotations.
Approach: They propose a continual pre-training approach to train deep learning models . they propose augmentation method and sequential self-distillation to boost performance .
Outcome: The proposed method outperforms methods that employ continual pre-training on labeled datasets on few-shot intent detection tasks.

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