| CPC G09B 19/06 (2013.01) [G09B 5/02 (2013.01); G10L 15/22 (2013.01); G10L 2015/226 (2013.01)] | 14 Claims |
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1. A system for strengths-weaknesses based clinical assessment and intervention for dyslexia comprising:
a database comprising a large-scale profile of a plurality of user performance sets across different domains;
a first subgroup generator for performing a theory-driven machine learning approach with respect to the database by obtaining a layer with nodes which are computed by summing all component values multiplied by factor loadings of component values using exploratory factor analysis, wherein subgroups are generated according to whether the nodes are activated;
a second subgroup generator for performing an integrated theory-and-data-driven machine learning approach with respect to the database by training a neural network applying a principal component analysis (PCA) via an encoder and a decoder, wherein a data set of each user is encoded to a three-dimensional vector by the encoder and clustering the users in a hierarchical clustering to group users based on the users' similarity or distance computed among the users;
a comparator comparing the theory-driven machine learning approach with the integrated theory-and-data-driven machine learning approach to determine whether the theory-driven machine learning approach aligns with the integrated theory-and-data-driven machine learning approach; and
a scoring module computing scores of the various domains with respect to users clustered in the different subgroups;
an intervention module to provide individualized intervention for each of the subgroups, such that the users in the different subgroups receive different interventions;
wherein the interventions comprise training in one or more domain-general cognitive and music skills, or language-specific listening, speaking, reading, writing, or combinations thereof.
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