MIT has developed a low cost system to identify speech and language disorders in very young children. These disorders are generally diagnosed post kindergarten, which means a delay in treatment and therapy for these children. MIT researchers have developed a computer system based on a simple test. Children are shown images and text, and are asked to explain the story in their own words. A recording of this speech is processed to identify disorders.
Jordan Green, a researcher for the MGH Institute of Health Professions said “Assessing children’s speech is particularly challenging because of high levels of variation even among typically developing children. You get five clinicians in the room and you might get five different answers.”
Machine Learning is used for the identification. A data set collected by researchers at the MGH Institute of Health Professions is used to train the artificial intelligence. The frequency and duration of pauses, as well as continuous speech is compared to this data set. The machine looks for patterns in this speech test, that matches with the known speech patterns of disorders. The system can be implemented in a smartphone, which allows for a large number of children to be screened for disorders at a very low cost.
MIT has developed a low cost system to identify speech and language disorders in very young children. These disorders are generally diagnosed post kindergarten, which means a delay in treatment and therapy for these children. MIT researchers have developed a computer system based on a simple test. Children are shown images and text, and are asked to explain the story in their own words. A recording of this speech is processed to identify disorders.
Jordan Green, a researcher for the MGH Institute of Health Professions said “Assessing children’s speech is particularly challenging because of high levels of variation even among typically developing children. You get five clinicians in the room and you might get five different answers.”
Machine Learning is used for the identification. A data set collected by researchers at the MGH Institute of Health Professions is used to train the artificial intelligence. The frequency and duration of pauses, as well as continuous speech is compared to this data set. The machine looks for patterns in this speech test, that matches with the known speech patterns of disorders. The system can be implemented in a smartphone, which allows for a large number of children to be screened for disorders at a very low cost.
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