Papers by Frédéric Béchet

2 papers
Handling Normalization Issues for Part-of-Speech Tagging of Online Conversational Text (L18-1)

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Challenge: a new approach to POS tagging noisy user generated text is proposed . word embeddings are trained on a noisy corpus to address both normalization and POS.
Approach: They propose to use word embeddings to normalize text before tagging it, while a gated neural network based tagger handles the remaining errors.
Outcome: The proposed approach normalizes some errors before tagging, while a gated neural network handles the remaining errors.
Robust Semantic Parsing with Adversarial Learning for Domain Generalization (N19-2)

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Challenge: Using adversarial learning to train models on a higher level of abstraction to increase their robustness to lexical and stylistic variations is crucial for the integration of Semantic Parsing technologies in real applications.
Approach: They propose to perform Semantic Parsing with a domain classification adversarial task and an unsupervised domain discovery approach that yields equivalent improvements.
Outcome: The proposed approach improves on a French corpus of encyclopedic documents annotated with FrameNet and an unsupervised domain discovery approach yields equivalent improvements.

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