ATCCaps is a call-sign-aware ATC speech dataset containing 202.94 hours of audio, 170385 utterances and 922 unique call signs, constructed via transcript parsing, ADS-B metadata, normalization, filtering and LLM captioning.
Adapting automatic speech recognition for accented air traffic control communications
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
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A consequence-aware evaluation framework applied to LLMs in ATC finds peak Risk Score of only 0.69 despite high macro-F1, with errors concentrated in high-impact entities.
citing papers explorer
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ATCCaps: A Call-Sign-Aware Speech Dataset for Air Traffic Control Recognition
ATCCaps is a call-sign-aware ATC speech dataset containing 202.94 hours of audio, 170385 utterances and 922 unique call signs, constructed via transcript parsing, ADS-B metadata, normalization, filtering and LLM captioning.
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Safety-Oriented Evaluation of Language Understanding Systems for Air Traffic Control
A consequence-aware evaluation framework applied to LLMs in ATC finds peak Risk Score of only 0.69 despite high macro-F1, with errors concentrated in high-impact entities.