Papers with fine-tuning monolingual

1 papers
PolyWER: A Holistic Evaluation Framework for Code-Switched Speech Recognition (2024.findings-emnlp)

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Challenge: Existing methods for measuring accuracy, such as Word Error Rate (WER), are too strict to address this challenge.
Approach: They propose a framework for evaluating speech recognition systems to handle language-mixing by appending annotations to a publicly available Arabic-English code-switched dataset.
Outcome: The proposed framework evaluates speech recognition systems against human judgement and a publicly available Arabic-English code-switched dataset.

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