Joseph Sabine, Iverson Paul, Manohar Sanjay, Fox Zoe, Scott Sophie K, Husain Masud
a Institute of Cognitive Neuroscience, University College London , London , UK.
Q J Exp Psychol (Hove). 2015;68(10):2022-40. doi: 10.1080/17470218.2014.1002799. Epub 2015 Mar 11.
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.
语音记忆是言语工作记忆(WM)模型的关键组成部分。但言语工作记忆的效果如何呢?大多数研究通过二元报告测量来评估这一点,以得出能够存储的固定项目数量。然而,视觉工作记忆的最新研究结果通过采用具有模拟反应量表的回忆精度测量方法,对这种“量化”观点提出了挑战。语音工作记忆可能依赖于连续和分类存储机制。我们使用一种新颖的语音匹配范式,测量了音素的工作记忆回忆精度。元音质量是从共振峰空间连续体中采样的。一个探测元音必须在连续的模拟反应量表上进行调整,以匹配目标元音的质量。至关重要的是,这提供了一个围绕其真实值的记忆表征变异性的指标,从而使我们能够估计记忆是如何从原始声音中扭曲的。记忆负荷以两种方式影响语音回忆的质量。首先,随着项目数量的增加,回忆精度逐渐下降,这与语音的工作记忆表征随着记忆中项目数量的增加而变得更嘈杂的观点一致,就像视觉一样。基于多维缩放(MDS),噪声水平似乎反映在共振峰空间的扭曲中。其次,随着记忆负荷的增加,有证据表明参与者的反应在特定元音周围的聚类程度更高。一个混合模型捕捉了连续和分类反应,表明随着工作记忆负荷的增加,从连续记忆向分类记忆转变。这表明直接声学存储可用于单个项目,但当必须存储更多项目时,必须使用分类表征。