Vector Representations of Idioms in Conversational Systems

نویسندگان

چکیده

In this study, we demonstrate that an open-domain conversational system trained on idioms or figurative language generates more fitting responses to prompts containing idioms. Idioms are a part of everyday speech in many languages and across cultures, but they pose great challenge for natural processing (NLP) systems involve tasks such as information retrieval (IR), machine translation (MT), artificial intelligence (AI). We utilized the Potential Idiomatic Expression (PIE)-English idiom corpus two investigated: classification conversation generation. achieved state-of-the-art (SoTA) result 98% macro F1 score task by using SoTA T5 model. experimented with three instances dialogue model—the Dialogue Generative Pre-trained Transformer (DialoGPT)—for Their performances were evaluated automatic metric, perplexity, human evaluation. The results showed model generated 71.9% time comparison similar was not corpus. have contributed checkpoint/demo/code HuggingFace hub public access.

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ژورنال

عنوان ژورنال: Sci

سال: 2022

ISSN: ['2413-4155']

DOI: https://doi.org/10.3390/sci4040037