Perceptual comparisons of adolescent stutterers' and nonstutterers' fluent speech

Numerous investigators have reported that listeners are able to perceptually differentiate adult stutterers' and nonstutterers' fluent speech productions. However, findings from similar studies with children ranging in age from 3 to 9 yr have indicated that perceptual discrimination of child stutterers is difficult. A logical extension of this line of investigation would be to determine when during maturation from childhood to adulthood stutterers' fluent speech becomes perceptibly different than nonstutterers'. Therefore, in this study similar fluent speech samples from seven 12–16-yr-old adolescent male stutterers and seven matched nonstutterers were analyzed perceptually in a paired stimulus paradigm by 15 sophisticated listeners. Individual subject analyses using signal detection theory revealed that five of the seven stutterers were discriminated. When averaged for subject group comparison, these findings indicated that listeners successfully discriminated between the fluent speech of the two groups. Therefore, the perceptual difference in fluent speech production reported previously for adults appears to be present by adolescence.     

Understanding fish cognition: a review and appraisal of current practices

Animal Cognition - With over 30,000 recognized species, fishes exhibit an extraordinary variety of morphological, behavioural, and life-history traits. The field of fish cognition has grown...     

Timing the “magical number seven”: Presentation rate and regularity affect verbal working memory performance

The informative value of time and temporal structure often remains neglected in cognitive assessments. However, next to information about stimulus identity we can exploit temporal ordering principles, such as regularity, periodicity, or grouping to generate predictions about the timing of future events. Such predictions may improve cognitive performance by optimising adaptation to dynamic stimuli. Here, we investigated the influence of temporal structure on verbal working memory by assessing immediate recall performance for aurally presented digit sequences (forward digit span) as a function of standard (1000 ms stimulus-onset-asynchronies, SOAs), short (700 ms), long (1300 ms) and mixed (700–1300 ms) stimulus timing during the presentation phase. Participant's digit spans were lower for short and mixed SOA presentation relative to standard SOAs. This confirms an impact of temporal structure on the classic “magical number seven,” suggesting that working memory performance can in part be regulated through the systematic application of temporal ordering principles.     

Does Religious Activity Distinguish the Mortality Experiences of Older Taiwanese? An Analysis Using Eighteen Years of Follow-Up Data

This paper extends investigation of religiosity and longevity to Taiwan using a 1989 survey: N = 3849, aged 60+, with 18 years of follow-up. Religious activity is measured as worship and performance of rituals. A Gompertz regression, adjusted and non-adjusted for covariates and mediating factors, shows the hazard of dying is lower for the religiously active versus the non-active. Transformed into life table functions, a 60-year-old religiously active Taiwanese female lives more than 1 year longer than her non-religious counterpart, ceteris paribus. Mainland Chinese migrants are examined carefully because of unique religious and health characteristics. They live longer, but the religiosity gap is similar.

     

EARSHOT: A Minimal Neural Network Model of Incremental Human Speech Recognition

Despite the lack of invariance problem (the many-to-many mapping between acoustics and percepts), human listeners experience phonetic constancy and typically perceive what a speaker intends. Most models of human speech recognition (HSR) have side-stepped this problem, working with abstract, idealized inputs and deferring the challenge of working with real speech. In contrast, carefully engineered deep learning networks allow robust, real-world automatic speech recognition (ASR). However, the complexities of deep learning architectures and training regimens make it difficult to use them to provide direct insights into mechanisms that may support HSR. In this brief article, we report preliminary results from a two-layer network that borrows one element from ASR, long short-term memory nodes, which provide dynamic memory for a range of temporal spans. This allows the model to learn to map real speech from multiple talkers to semantic targets with high accuracy, with human-like timecourse of lexical access and phonological competition. Internal representations emerge that resemble phonetically organized responses in human superior temporal gyrus, suggesting that the model develops a distributed phonological code despite no explicit training on phonetic or phonemic targets. The ability to work with real speech is a major advance for cognitive models of HSR.     

Talking Points: A Modulating Circle Increases Listening Effort Without Improving Speech Recognition in Young Adults

Psychonomic Bulletin & Review - Speech recognition is improved when the acoustic input is accompanied by visual cues provided by a talking face (Erber in Journal of Speech and Hearing Research,...