Papers by Adrien Pupier

3 papers
Growing Trees on Sounds: Assessing Strategies for End-to-End Dependency Parsing of Speech (2024.acl-short)

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Challenge: Direct dependency parsing of the speech signal is proposed as a way of incorporating prosodic information into the parser and bypassing the limitations of a pipeline approach.
Approach: They propose to use graph-based parsing and sequence labeling based parses to integrate prosodic information into the parser and bypass limitations of pipeline approaches.
Outcome: The proposed graph based approach outperforms a pipeline approach on a large treebank of spoken french, despite having 30% fewer parameters.
Jargon: A Suite of Language Models and Evaluation Tasks for French Specialized Domains (2024.lrec-main)

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Challenge: Pretrained language models are the de facto backbone of most state-of-the-art NLP systems.
Approach: They propose a family of domain-specific pretrained PLMs for French focusing on three important domains: transcribed speech, medicine, and law.
Outcome: The proposed models perform better on transcribed speech, medicine, and law domains than state-of-the-art models on a diverse set of tasks and datasets.
What Has LeBenchmark Learnt about French Syntax? (2024.lrec-main)

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Challenge: Pretrained acoustic models are increasingly used for downstream speech tasks such as automatic speech recognition, speech translation, spoken language understanding or speech parsing.
Approach: They propose to probing a pretrained acoustic model for French for syntactic information using the Orféo treebank.
Outcome: The proposed model is trained on 7k hours of spoken French and obtained reasonable results on tasks that require higher level linguistic knowledge.

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