Khayr Ranin, Karawani Hanin, Banai Karen
Department of Communication Sciences and Disorders, Faculty of Social Welfare and Health Sciences, University of Haifa, Haifa, Israel.
Front Psychol. 2023 Sep 7;14:1238823. doi: 10.3389/fpsyg.2023.1238823. eCollection 2023.
Individual differences in speech recognition in challenging listening environments are pronounced. Studies suggest that implicit learning is one variable that may contribute to this variability. Here, we explored the unique contributions of three indices of implicit learning to individual differences in the recognition of challenging speech. To this end, we assessed three indices of implicit learning (perceptual, statistical, and incidental), three types of challenging speech (natural fast, vocoded, and speech in noise), and cognitive factors associated with speech recognition (vocabulary, working memory, and attention) in a group of 51 young adults. Speech recognition was modeled as a function of the cognitive factors and learning, and the unique contribution of each index of learning was statistically isolated. The three indices of learning were uncorrelated. Whereas all indices of learning had unique contributions to the recognition of natural-fast speech, only statistical learning had a unique contribution to the recognition of speech in noise and vocoded speech. These data suggest that although implicit learning may contribute to the recognition of challenging speech, the contribution may depend on the type of speech challenge and on the learning task.
在具有挑战性的听力环境中,语音识别的个体差异十分显著。研究表明,内隐学习是可能导致这种变异性的一个变量。在此,我们探讨了内隐学习的三个指标对挑战性语音识别中个体差异的独特贡献。为此,我们在一组51名年轻成年人中评估了内隐学习的三个指标(知觉性、统计性和偶然性)、三种挑战性语音(自然快速语音、声码语音和噪声中的语音)以及与语音识别相关的认知因素(词汇、工作记忆和注意力)。将语音识别建模为认知因素和学习的函数,并从统计学上分离出每个学习指标的独特贡献。这三个学习指标互不相关。虽然所有学习指标对自然快速语音的识别都有独特贡献,但只有统计学习对噪声中的语音和声码语音的识别有独特贡献。这些数据表明,尽管内隐学习可能有助于挑战性语音的识别,但这种贡献可能取决于语音挑战的类型和学习任务。