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About

Alice Baird is a leading researcher at the intersection of affective computing, speech processing, and clinical applications for autism spectrum conditions. Her work focuses on developing automatic recognition systems for atypical vocalizations and emotional expressions, particularly in autistic children. Baird’s major contributions include creating novel datasets of autistic child vocalizations and pioneering classification methods—such as convolutional recurrent neural networks—to detect echolalia and other atypical speech patterns. Her 2018 paper on emotional expression in psychiatric conditions, with 83 citations, has become a key reference for clinicians exploring new technologies for assessment. Baird’s research on voice activity detection’s impact on speech emotion recognition (21 citations) and her work on empathy recognition in human-robot interaction further demonstrate her commitment to improving assistive technologies. By combining machine learning with deep understanding of neurodevelopmental conditions, Baird’s work directly supports the development of adaptive, user-sensitive robots for educational and therapeutic settings. Her studies consistently bridge computational innovation and real-world clinical need, making her a pivotal figure in affective computing for autism.