Papers with parameter estimation

3 papers
Common Phone: A Multilingual Dataset for Robust Acoustic Modelling (2022.lrec-1)

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Challenge: Current state-of-the-art acoustic models can easily comprise more than 100 million parameters.
Approach: They propose to train a gender-balanced, multilingual corpus from 76.000 contributors via Mozilla’s Common Voice project to perform phonetic symbol recognition and validate the quality of the generated phonetic annotation.
Outcome: The proposed model can perform phonetic symbol recognition and validate the quality of the generated phonetic annotation.
Unsupervised Discontinuous Constituency Parsing with Mildly Context-Sensitive Grammars (2023.acl-long)

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Challenge: a recent study shows that context-free grammars are not natural for modeling discontinuous language phenomena such as extrapositions and cross-serial dependencies.
Approach: They propose a grammar induction approach with mildly context-sensitive grammars for unsupervised discontinuous parsing.
Outcome: Experiments on German and Dutch show that the proposed grammar induction method is beneficial for unsupervised parsing.
Bayesian Learning for Neural Dependency Parsing (N19-1)

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Challenge: Several approaches for dependency parsing in the small data regime have been proposed.
Approach: They propose to use stochastic gradient Langevin dynamics to generate samples from the approximated posterior to overcome the computational and statistical costs of the approximate inference step.
Outcome: The proposed model outperforms the biaffine model on 6 languages with less than 5k training instances and improves across five languages.

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