AIMC Topic: Language Development Disorders

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Early Identification of Language Disorders Using Natural Language Processing and Machine Learning: Challenges and Emerging Approaches.

Journal of speech, language, and hearing research : JSLHR Jan 9, 2025
PURPOSE: Recent advances in artificial intelligence provide opportunities to capture and represent complex features of human language in a more automated manner, offering potential means of improving the efficiency of language assessment. This review...
Machine Learning Child Humans Language Tests Natural Language Processing Language Disorders Language Development Disorders Early Diagnosis
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Identifying Children With Clinical Language Disorder: An Application of Machine-Learning Classification.

Journal of learning disabilities May 7, 2019
In this study, we identified child- and family-level characteristics most strongly associated with clinical identification of language disorder for preschool-aged children. We used machine learning to identify variables that best classified children ...
Humans Language Therapy Outcome Assessment, Health Care Male Machine Learning Early Diagnosis Child, Preschool Female Early Medical Intervention Language Development Disorders
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Automatic classification of 6-month-old infants at familial risk for language-based learning disorder using a support vector machine.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology Apr 12, 2016
OBJECTIVES: This study assesses the ability of a novel, "automatic classification" approach to facilitate identification of infants at highest familial risk for language-learning disorders (LLD) and to provide converging assessments to enable earlier...
Humans Electroencephalography Language Development Disorders Female Infant Child, Preschool Male Case-Control Studies Support Vector Machine
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What can Neighbourhood Density effects tell us about word learning? Insights from a connectionist model of vocabulary development.

Journal of child language Feb 17, 2016
In this paper, we investigate the effect of neighbourhood density (ND) on vocabulary size in a computational model of vocabulary development. A word has a high ND if there are many words phonologically similar to it. High ND words are more easily lea...
Language Development Disorders Language Phonetics Learning Language Development Machine Learning Probability Computer Simulation Vocabulary Humans Neural Networks, Computer
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Predicting Language Difficulties in Middle Childhood From Early Developmental Milestones: A Comparison of Traditional Regression and Machine Learning Techniques.

Journal of speech, language, and hearing research : JSLHR Aug 8, 2018
PURPOSE: The current study aimed to compare traditional logistic regression models with machine learning algorithms to investigate the predictive ability of (a) communication performance at 3 years old on language outcomes at 10 years old and (b) bro...
Logistic Models Predictive Value of Tests Child, Preschool Child Language Development Disorders Language Tests Child Language Machine Learning Algorithms Female Male Humans
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Mapping the Early Language Environment Using All-Day Recordings and Automated Analysis.

American journal of speech-language pathology May 17, 2017
PURPOSE: This research provided a first-generation standardization of automated language environment estimates, validated these estimates against standard language assessments, and extended on previous research reporting language behavior differences...
Tape Recording Language Development Disorders Mother-Child Relations Humans Semantics Socioeconomic Factors Female Natural Language Processing Vocabulary Educational Status Social Environment Male Communication Verbal Behavior Child, Preschool
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