The Meaning Intelligence Framework raises zero-shot register classification accuracy from 33.3% to 73.3% on a 30-item Nigerian discourse calibration set while showing that smaller models can outperform larger ones on cultural competence.
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Audio language models are benchmarked on five semantic and paralinguistic reasoning tasks to reveal limitations in handling spoken audio evidence, accent variation, and domain shifts.
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The Register Gap: A Meaning Intelligence Framework for Nigerian Public Discourse
The Meaning Intelligence Framework raises zero-shot register classification accuracy from 33.3% to 73.3% on a 30-item Nigerian discourse calibration set while showing that smaller models can outperform larger ones on cultural competence.
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Afrispeech Semantics: Evaluating Audio Semantic Reasoning in Spoken Language Models Across Domains and Accents
Audio language models are benchmarked on five semantic and paralinguistic reasoning tasks to reveal limitations in handling spoken audio evidence, accent variation, and domain shifts.