Papers by Hugo Laurençon

2 papers
The ROOTS Search Tool: Data Transparency for LLMs (2023.acl-demo)

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Challenge: a 1.6TB multilingual text corpus is currently the largest language model . large language models are ubiquitous in modern NLP, used directly to generate text and as building blocks in downstream applications.
Approach: They propose a search engine for the 1.6TB multilingual ROOTS corpus offering both fuzzy and exact search capabilities.
Outcome: The ROOTS Search Tool is an open-source search engine for the 1.6TB multilingual ROOTs corpus.
DP-Parse: Finding Word Boundaries from Raw Speech with an Instance Lexicon (2022.tacl-1)

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Challenge: Existing nonparametric models for text segmentation use a Dirichlet process to jointly segment sentences and build a lexicon of word types.
Approach: They propose a Bayesian nonparametric model that uses a Dirichlet process to jointly segment sentences and build a lexicon of word types.
Outcome: The proposed model improves on the Zero Resource Speech Benchmark 2017 and can learn semantic and syntactic representations as assessed by a new spoken word embedding benchmark.

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