Precision of working memory for speech sounds

Abstract

Memory for speech sounds is a key component of models of verbal working memory (WM). But how good is verbal WM? Most investigations assess this using binary report measures to derive a fixed number of items that can be stored. However, recent findings in visual WM have challenged such “quantized” views by employing measures of recall precision with an analogue response scale. WM for speech sounds might rely on both continuous and categorical storage mechanisms. Using a novel speech matching paradigm, we measured WM recall precision for phonemes. Vowel qualities were sampled from a formant space continuum. A probe vowel had to be adjusted to match the vowel quality of a target on a continuous, analogue response scale. Crucially, this provided an index of the variability of a memory representation around its true value and thus allowed us to estimate how memories were distorted from the original sounds. Memory load affected the quality of speech sound recall in two ways. First, there was a gradual decline in recall precision with increasing number of items, consistent with the view that WM representations of speech sounds become noisier with an increase in the number of items held in memory, just as for vision. Based on multidimensional scaling (MDS), the level of noise appeared to be reflected in distortions of the formant space. Second, as memory load increased, there was evidence of greater clustering of participants’ responses around particular vowels. A mixture model captured both continuous and categorical responses, demonstrating a shift from continuous to categorical memory with increasing WM load. This suggests that direct acoustic storage can be used for single items, but when more items must be stored, categorical representations must be used.