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Beyond WER: Entity and Disfluency Recall in Accented Conversational ASR
Author1, Author2, Author3, Author4, Author5
ASRentity recognitionfine-tuningaccented speech
2609.20828
Builder Relevance
1h ago80%
Abstract
This paper presents a novel pipeline for improving entity and disfluency recall in accented conversational ASR systems.
Reality Card
Core Claim
The proposed pipeline achieves 80-85% entity recall and 76-86% filler recall, significantly improving upon previous benchmarks.
Method / Result
Entity recall improved from 53-55% to 80-85% and filler recall from <5% to 76-86%.
Limitations
The study's results may be limited to the specific accents and regions tested, potentially affecting generalizability.
Paper to code
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