A Rational Analysis of the Speech-to-Song Illusion
This work addresses a long-standing psychological phenomenon with potential applications in understanding human perception and AI language processing, though it is incremental in extending the illusion to text-based contexts.
The researchers tackled the speech-to-song illusion by developing a formal statistical inference model to explain why repeated spoken sentences sound more musical, and they introduced a novel prose-to-lyrics illusion where duplicating written sentences makes them appear more like song lyrics, supported by evidence from human participants and large language models.
The speech-to-song illusion is a robust psychological phenomenon whereby a spoken sentence sounds increasingly more musical as it is repeated. Despite decades of research, a complete formal account of this transformation is still lacking, and some of its nuanced characteristics, namely, that certain phrases appear to transform while others do not, is not well understood. Here we provide a formal account of this phenomenon, by recasting it as a statistical inference whereby a rational agent attempts to decide whether a sequence of utterances is more likely to have been produced in a song or speech. Using this approach and analyzing song and speech corpora, we further introduce a novel prose-to-lyrics illusion that is purely text-based. In this illusion, simply duplicating written sentences makes them appear more like song lyrics. We provide robust evidence for this new illusion in both human participants and large language models.