Papers by Melinda Fricke

1 papers
Speaker Information Can Guide Models to Better Inductive Biases: A Case Study On Predicting Code-Switching (2022.acl-long)

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Challenge: Prior approaches for predicting code-switching only consider shallow linguistic context.
Approach: They hypothesize that enriching models with speaker information can guide them to pick up on relevant inductive biases.
Outcome: The proposed model improves on a speaker-driven task in English–Spanish bilingual dialogues by adding sociolinguistically-grounded speaker features as prepended prompts.

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