Accent Classification
A task in speech processing that aims to automatically identify the accent type of a speaker. It is commonly applied in scenarios such as adaptive optimization of automatic speech recognition systems and linguistic research.
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When there is speaker overlap between the training set and test set, an accent classification model may learn to recognize specific speakers rather than accent features, leading to inflated evaluation results.
The study advocates that robust accent classification evaluation should incorporate both speaker-isolated evaluation and cross-corpus testing.
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When there is speaker overlap between the training set and test set, an accent classification model may learn to recognize specific speakers rather than accent features, leading to inflated evaluation results.
50%UnverifiedThe study advocates that robust accent classification evaluation should incorporate both speaker-isolated evaluation and cross-corpus testing.
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