Introduces ontology memory-augmented ASR correction that organizes prior interaction history into retrievable nodes and reports gains over direct correction in 9 of 10 backbone-setting pairs on a new long-context dataset.
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A survey that classifies non-intrusive ASR refinement methods into five categories, reviews domain adaptation and evaluation datasets, proposes standardized metrics, and identifies future research directions.
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Ontology Memory-Augmented ASR Correction for Long Text-Speech Interleaved Conversations
Introduces ontology memory-augmented ASR correction that organizes prior interaction history into retrievable nodes and reports gains over direct correction in 9 of 10 backbone-setting pairs on a new long-context dataset.