SOURCE-LINKED INTELLIGENCE
Reasoning Beyond Transcription: Audio Language Models on Child Stuttering Speech
Child speech differs from adult speech in acoustics, prosody, and linguistic structures. Speech disfluencies (such as repetitions) further challenge automatic understanding. While Audio Language Models (ALMs) show strong semantic reasoning from speech audio, their ability to reason about disfluent child speech in mixed-speaker settings remains unexplored. We investigate this through two tasks: child-focused semantic summarization and speech entailment. Experiments use recordings of children who stutter in mixed speaker interviews without explicit speaker separation. Models are instruction-guid
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-07T20:44:38.000Z
First collected: 2026-09-20T20:32:20.942Z. This is not the publication date.