Papers with conservative data filtering

1 papers
Robust ASR Error Correction with Conservative Data Filtering (2024.emnlp-industry)

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Challenge: Error correction (EC) based on large language models is an emerging technology to enhance the performance of automatic speech recognition systems.
Approach: They propose to pair large set of ASR hypotheses with gold references to improve linguistic acceptability over sources and be inferable from available context.
Outcome: The proposed approach significantly reduces overcorrection and improves quality in out-of-domain (OOD) settings.

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