Purpose Working memory (WM) deficits are implicated in various communication disorders, including stuttering. The reading span test (RST) measures WM capacity with the dual task of reading sentences aloud and remembering target words. This study demonstrates a difference in strategy between people who stutter (PWS) and people who do not stutter (PWNS) in performing the RST. The impact of the effective strategy and the stuttering-like disfluencies during the RST were investigated. Method Twenty-six PWS and 24 people who do not stutter performed the RST and a simple reading aloud task. After the RST, they were asked which strategy (“imagery” or “rehearsal”) they had used in order to remember the target words during the task. Results The proportion of those who used an “imagery” strategy during the RST was significantly smaller in the PWS group. However, the RST scores of those who used an “imagery” strategy were significantly higher than the RST scores of those who used a “rehearsal” strategy in both groups. The “rehearsal” users were asked to undertake one more RST with an “imagery” strategy, which resulted in an increased score for both groups. The disfluency frequency of the PWS group was significantly reduced during the RST than during the oral reading task, irrespective of the employed strategy. Conclusions PWS tended to use the less effective verbal “rehearsal” strategy during the RST. The differential effects of switching strategies on the measured WM capacity and on the disfluency rate suggest that the enhanced fluency during the RST would be mostly attributable to the reduced attention to speech motor control. Therefore, the use of the “imagery” strategy and focusing on the contents of communication, away from speech motor control, should help PWS communicate better in daily conversation.
In the context of big data, traditional collaborative filtering recommendation algorithms cannot provide users with accurate recommendation services, making the sparsity of user data become an important factor affecting the accuracy of recommendation in the complex social network environment. This paper mainly studies the design and application of travel service recommendation algorithm based on cloud computing. In this paper, the data is processed based on MapReduce parallel computing framework to improve the performance and speed of the algorithm. The Linux-equipped cluster is deployed under the Hadoop framework. The cluster feasibility test is carried out to realize the recommendation function of the algorithm, and the function of the algorithm is realized according to the actual problems. On the Hadoop big data platform, the traditional algorithm was improved and the hadoop-based collaborative filtering recommendation algorithm was implemented to further improve the recommendation rate and accuracy of the traditional recommendation filtering algorithm.
The present study investigated the short-term effects of speech shadowing training in 16 people who stutter (PWS). Speech shadowing is a task in which subjects listen to a spoken passage and repeat it with the shortest possible delay. In a subgroup of 8 PWS whose reading contained more than 3% of stuttered phrases before shadowing, the frequency of stuttering, especially blocking, and the mean duration of stuttering symptoms decreased during shadowing. They also produced significantly fewer dysfluencies in the reading-aloud task after shadowing than in the initial reading task, regardless of use of the same or different reading materials. The other 8 PWS with fewer than 3% dysfluencies before shadowing showed no significant change in stuttering frequency during or after shadowing. Thus, speech shadowing has a short-term aftereffect of reducing the frequency of stuttering, as well as possible usefulness by giving a chance to those with frequent symptoms to experience fluent speech during training. Analysis of the participants' free comments after the training based on the KJ (card sorting) method showed that they felt their speech was more fluent during shadowing than usual, and that they were looking forward to more shadowing training.
The present study investigated the relationship between working memory capacity (WMC) and shadowing latency in 21 people who stutter (PWS) and 15 people who do not stutter (PWNS). WMC was measured using the Reading Span Test (RST). The mean RST score of the PWS group was significantly lower than that of the PWNS group. The PWS group also showed significantly shorter shadowing latency than the PWNS group. In terms of the relationship between WMC and shadowing latency, the PWS group had a significant positive correlation, whereas the PWNS group showed a significant negative correlation. These results suggest that PWS and PWNS employ different processing strategies in verbal working memory and shadowing tasks.
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