AINeutralarXiv – CS AI · Apr 106/10
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In-Context Learning in Speech Language Models: Analyzing the Role of Acoustic Features, Linguistic Structure, and Induction Heads
Researchers investigate in-context learning (ICL) in speech language models, revealing that speaking rate significantly affects model performance and acoustic mimicry, while induction heads play a causal role identical to text-based ICL. The study bridges the gap between text and speech domains by analyzing how models learn from demonstrations in text-to-speech tasks.