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An iterative probabilistic model of speech-related vocalization rate growth due to child-caregiver interaction

机译:儿童护理人员互动引起的语音相关发声率增长的迭代概率模型

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Over the course of the first four years of life, the proportion of children's vocalizations that are speech-related increases steadily. The rate of this growth is reduced for children with autism spectrum disorder (ASD) and for children from households with relatively lower socioeconomic status (SES). The present study attempts to model this set of findings, treating adult responses as reinforcers of child behavior. The model starts with a 50% chance of producing a speech-related vocalization and gradually increases this probability by updating its speechrelated vocalization and not-speech-related vocalization probabilities each time a response is received. Numbers of vocalizations per day and rates of adult responding to the two vocalization types are drawn from human data to create high SES typically developing (TD), high SES ASD, low SES TD, and low SES ASD versions. The model shows growth in speech-related vocalizations that matches well to that observed for the human children and that matches the differences observed across clinical and SES groups. Some aspects of speech-related vocalization development are not well accounted for by the model; possible explanations and extensions are proposed.
机译:在生命的前四年的过程中,与语音相关的儿童发声比例稳步增加。自闭症谱系障碍(ASD)的儿童和社会经济地位较低(SES)的儿童减少这种增长的速率。本研究试图模拟这套调查结果,将成年反应视为儿童行为的增强剂。该模型以50%的几率开始产生与语音相关的发声,并且每次收到响应时都会通过更新其语音相关的发声和非语音相关的发声概率来逐渐增加这种概率。每天的发声数量和成人响应两种发声类型的率来自人类数据,以创建高SES,通常是开发(TD),高SES ASD,低SES TD和低SES ASD版本。该模型显示出与人类儿童观察到的与观察到的语音相关发声的增长,并且与临床和SES组织观察到的差异相匹配。语音相关的发声开发的某些方面并不适用于该模型;提出了可能的解释和扩展。

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