Yumba Wycliffe Kabaywe
Department of Behavioral Sciences and Learning, Linköping UniversityLinköping, Sweden.
Linnaeus Centre HEAD, Swedish Institute for Disability Research, Linköping UniversityLinköping, Sweden.
Front Psychol. 2017 Aug 15;8:1308. doi: 10.3389/fpsyg.2017.01308. eCollection 2017.
Previous studies have demonstrated that successful listening with advanced signal processing in digital hearing aids is associated with individual cognitive capacity, particularly working memory capacity (WMC). This study aimed to examine the relationship between cognitive abilities (cognitive processing speed and WMC) and individual listeners' responses to digital signal processing settings in adverse listening conditions. A total of 194 native Swedish speakers (83 women and 111 men), aged 33-80 years (mean = 60.75 years, = 8.89), with bilateral, symmetrical mild to moderate sensorineural hearing loss who had completed a lexical decision speed test (measuring cognitive processing speed) and semantic word-pair span test (SWPST, capturing WMC) participated in this study. The Hagerman test (capturing speech recognition in noise) was conducted using an experimental hearing aid with three digital signal processing settings: (1) linear amplification without noise reduction (NoP), (2) linear amplification with noise reduction (NR), and (3) non-linear amplification without NR ("fast-acting compression"). The results showed that cognitive processing speed was a better predictor of speech intelligibility in noise, regardless of the types of signal processing algorithms used. That is, there was a stronger association between cognitive processing speed and NR outcomes and fast-acting compression outcomes (in steady state noise). We observed a weaker relationship between working memory and NR, but WMC did not relate to fast-acting compression. WMC was a relatively weaker predictor of speech intelligibility in noise. These findings might have been different if the participants had been provided with training and or allowed to acclimatize to binary masking noise reduction or fast-acting compression.
先前的研究表明,数字助听器中先进的信号处理技术实现的成功听力与个体认知能力相关,尤其是工作记忆容量(WMC)。本研究旨在考察在不利听力条件下认知能力(认知处理速度和WMC)与个体听众对数字信号处理设置的反应之间的关系。共有194名瑞典语母语者(83名女性和111名男性)参与了本研究,他们年龄在33 - 80岁之间(平均年龄 = 60.75岁,标准差 = 8.89),患有双侧对称的轻度至中度感音神经性听力损失,且已完成词汇决策速度测试(测量认知处理速度)和语义单词对跨度测试(SWPST,测量WMC)。使用一款带有三种数字信号处理设置的实验性助听器进行了哈格曼测试(测量噪声中的语音识别):(1)无降噪的线性放大(NoP),(2)有降噪的线性放大(NR),以及(3)无NR的非线性放大(“快速压缩”)。结果表明,无论使用何种信号处理算法类型,认知处理速度都是噪声中语音清晰度的更好预测指标。也就是说,认知处理速度与NR结果和快速压缩结果(在稳态噪声中)之间的关联更强。我们观察到工作记忆与NR之间的关系较弱,但WMC与快速压缩无关。WMC是噪声中语音清晰度相对较弱的预测指标。如果为参与者提供训练和/或允许他们适应二元掩蔽降噪或快速压缩,这些结果可能会有所不同。