Papers by Gabriela Hernandez

1 papers
Reducing cohort bias in natural language understanding systems with targeted self-training scheme (2023.acl-industry)

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Challenge: In deep learning models, it is hard to capture all the variations of the language that different users can use.
Approach: They propose a framework that uses four active learning strategies to identify important samples coming from new users and a self training phase where a teacher model is trained from the first phase to expand the training data with relevant cohort utterances.
Outcome: The proposed framework reduces the bias related to new customers in a digital voice assistant system by using two phases: a fixing phase and a self training phase.

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