2023
Large-scale Investigations of AAC Usage Patterns: Trends, Autism, and Stacked Autoencoders
Atyabi A, Boccanfuso L, Snider J, Kim M, Barney E, Ahn Y, Li B, Dommer K, Shic F. Large-scale Investigations of AAC Usage Patterns: Trends, Autism, and Stacked Autoencoders. 2023, 00: 851-859. DOI: 10.1109/ccwc57344.2023.10099096.Peer-Reviewed Original ResearchAutism spectrum disorderAAC appSpeech-generating deviceUsage patternsLearning methodsDeep learning methodsStreams of dataUnsupervised learning methodIndividual usage patternsData modeling perspectiveNon-speech communicationData streamsData scienceStacked AutoencoderClassification accuracyModeling mechanismSpectrum disorderLanguage learningAlternative communication applicationPattern modelingAppsNumeric valuesFreeSpeechCommunication applicationsWealth of information
2017
An Exploratory Analysis Targeting Diagnostic Classification of AAC App Usage Patterns
Atyabi A, Li B, Ahn Y, Kim M, Barney E, Shic F. An Exploratory Analysis Targeting Diagnostic Classification of AAC App Usage Patterns. 2017, 1633-1640. DOI: 10.1109/ijcnn.2017.7966047.Peer-Reviewed Original ResearchAutism spectrum disorderSpeech-generating deviceFeature representationAAC appUsage patternsData mining perspectiveStreams of dataApp usage patternsAlternative communication (AAC) appData modelling techniquesIndividual usage patternsSupport vector machineMassive streamsData miningMining perspectiveData streamsEnsemble learningAbove chanceSpectrum disorderLearning methodsVector machineLanguage learningEveryday scenariosUsage profilesPrediction performance