Published multiple papers on topics such as simulating infant language acquisition, models of early word acquisition based on realistic-scale audiovisual naming events, exploring prenatal language exposure in computational models, introducing meta-analysis in evaluating computational models of infant language development, and developing intelligent wearables to track developing motor abilities in infants.
Research Experience
Leads the Speech and Cognition research group, which primarily uses computational modeling combining signal processing and machine learning to address these questions. Additionally, works on developing tools for automatic detection of neurophysiological problems in infants and technological means for large-scale audio- and language data analysis.
Education
No specific educational background information provided
Background
Research interests include how children learn to understand and produce speech without explicit teaching, which aspects of language development are innate to our brains and bodies, and how much can be learned from the environment using generic cognitive skills. Also interested in making machines use and understand language like humans do, not just through textual representations but by truly understanding and communicating meanings in the signal.