Papers by Kouki Miyazawa

1 papers
Quality Estimation for Partially Subjective Classification Tasks via Crowdsourcing (2020.lrec-1)

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Challenge: a common approach to quality estimation is to ask multiple reviewers to evaluate the same artifacts.
Approach: They propose a probabilistic model for subjective classification tasks that incorporates the qualities of artifacts as well as the abilities and biases of creators and reviewers as latent variables to be jointly inferred.
Outcome: The proposed model estimates the quality of speech more effectively than a vote aggregation, measured by correlation with a fine-grained classification by experts.

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