Suppr超能文献

利用声学、语音和词汇变量预测听力正常的年轻听众在噪声中的单词识别表现。

Predicting word-recognition performance in noise by young listeners with normal hearing using acoustic, phonetic, and lexical variables.

作者信息

McArdle Rachel, Wilson Richard H

机构信息

Bay Pines VA Healthcare System, Bay Pines, FL 33744, USA.

出版信息

J Am Acad Audiol. 2008 Jun;19(6):507-18. doi: 10.3766/jaaa.19.6.6.

Abstract

PURPOSE

To analyze the 50% correct recognition data that were from the Wilson et al (this issue) study and that were obtained from 24 listeners with normal hearing; also to examine whether acoustic, phonetic, or lexical variables can predict recognition performance for monosyllabic words presented in speech-spectrum noise.

RESEARCH DESIGN

The specific variables are as follows: (a) acoustic variables (i.e., effective root-mean-square sound pressure level, duration), (b) phonetic variables (i.e., consonant features such as manner, place, and voicing for initial and final phonemes; vowel phonemes), and (c) lexical variables (i.e., word frequency, word familiarity, neighborhood density, neighborhood frequency).

DATA COLLECTION AND ANALYSIS

The descriptive, correlational study will examine the influence of acoustic, phonetic, and lexical variables on speech recognition in noise performance.

RESULTS

Regression analysis demonstrated that 45% of the variance in the 50% point was accounted for by acoustic and phonetic variables whereas only 3% of the variance was accounted for by lexical variables. These findings suggest that monosyllabic word-recognition-in-noise is more dependent on bottom-up processing than on top-down processing.

CONCLUSIONS

The results suggest that when speech-in-noise testing is used in a pre- and post-hearing-aid-fitting format, the use of monosyllabic words may be sensitive to changes in audibility resulting from amplification.

摘要

目的

分析来自威尔逊等人(本期)研究的50%正确识别数据,这些数据由24名听力正常的听众提供;同时检验声学、语音或词汇变量是否能够预测在语谱噪声中呈现的单音节词的识别表现。

研究设计

具体变量如下:(a)声学变量(即有效均方根声压级、时长),(b)语音变量(即辅音特征,如首音和尾音的发音方式、发音部位和浊音;元音音素),以及(c)词汇变量(即词频、词熟悉度、邻域密度、邻域频率)。

数据收集与分析

描述性相关性研究将检验声学、语音和词汇变量对噪声中语音识别表现的影响。

结果

回归分析表明,在50%正确识别率这一点上,45%的方差由声学和语音变量解释,而只有3%的方差由词汇变量解释。这些发现表明,噪声中单音节词的识别更多地依赖自下而上的加工而非自上而下的加工。

结论

结果表明,当以佩戴助听器前后的形式进行噪声中言语测试时,使用单音节词可能对放大导致的可听度变化敏感。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验