Using Mimicry to Learn about Mental Representations

TL;DR

This paper investigates whether discrete phonological representations are useful for intonation by using mimicry experiments, finding that attractor-based models with detailed memory better explain speech than discrete signs.

Contribution

It demonstrates that discrete intonational phonology may not reflect actual speech representations, proposing attractor models as a more accurate alternative.

Findings

Discrete signs are not useful for intonation contours

Memory retains detailed information about utterances

Attractor models better explain speech production

Abstract

Phonology typically describes speech in terms of discrete signs like features. The field of intonational phonology uses discrete accents to describe intonation and prosody. But, are such representations useful? The results of mimicry experiments indicate that discrete signs are not a useful representation of the shape of intonation contours. Human behaviour seems to be better represented by a attractors where memory retains substantial fine detail about an utterance. There is no evidence that discrete abstract representations that might be formed that have an effect on the speech that is subsequently produced. This paper also discusses conditions under which a discrete phonology can arise from an attractor model and why - for intonation - attractors can be inferred without the implying a discrete phonology.