Speech perception with temporally patterned noise maskers.

Maury Courtland, Louis L. Goldstein,Jason D Zevin

semanticscholar(2019)

引用 0|浏览2
暂无评分
摘要
In the real world, speech perception frequently occurs under adverse listening conditions. Laboratory studies have identified distinct phenomena associated with more or less constant sources of noise (energetic masking), and competing verbal information (informational masking). One issue complicating direct comparisons between them is that common paradigms for studying energetic and informational masking di↵er along many dimensions, in particular, informational masking is almost always measured using linguistically meaningful information. We have developed a paradigm that uses temporally patterned noise, with the goal of comparing energetic and informational masking under more comparable conditions. We hypothesized that listeners would be able to take advantage of the structure in the masking noise, providing a processing advantage over energetic masking. The initial experiment provides strong evidence for this hypothesis, but conceptual replications did not produce the same pattern of results – at least with respect to measures of central tendency. A direct replication of the first experiment did not replicate the large di↵erences in the means but a final experiment strengthening the e↵ect did. Interestingly, however, exploratory analyses across all five experiments reveal robust evidence that patterned noise conditions produce increased individual variability. Further, we observed strong correlations, specifically between the patterned conditions. We attribute these findings to as yet unidentified cognitive ability di↵erences allowing some participants to benefit from the use of additional temporal information while others are hurt by the addition of unusable distracting information. Hypothesized predictive measures of task performance, such as working memory, inhibitory control, and musical experience did not correlate with performance, however.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要