SAIL focuses on human-centered signal & information processing that address key societal needs. Bridging science and engineering, SAILers pioneer behavioral signal processing and behavioral machine intelligence, affective computing, multimodal signal processing, computational media intelligence and computational speech science.
SAIL enables these through fundamental advances in audio, speech, language, image, video and bio signal processing, human and environment sensing and imaging, human-centered machine learning as well as applications developing speech, human language technologies, conversational and multimodal systems.
SAIL was established in 2000 by Professor Shrikanth (Shri) Narayanan and has made sustained contributions to numerous award winning papers, widely-used community resources, and broad impact through media mentions.
SAIL acknoweldges sustained support from federal agencies (NSF, NIH, DARPA, IARPA, DoD, ONR, DoJ etc), foundations as well as industry grants and contracts..
speech imaging, magnetic resonance imaging for dynamic vocal tract shaping and anatomy, understanding individual variability, speech development in children, prosody, articulatory-acoustic modeling, vocal song production/singing, clinical applications including neurological disoders and cancer
all aspects of the speech analysis/speech processing pipeline, speech and speaker recognition, diarization, spoken language processing, speech translation, computational prosody, multilingual speech and language processing, applications in defense and intelligence, health and the arts
multimodal processing of audio (including music, speech, and environmental audio), image, video, and text, computational modeling of media content and its impact on individuals and society, applications in entertainment media (movies, TV , ads), news, social media, user generated content
computational methods for illuminating behavioral traits and mental states for supporting decision making and actionable intelligence by humans and machines, tools for scientific discovery in behavioral phenotyping and behavior change modeling, applications in behavioral and mental health research and clinical translation (Addiction, Couple and Family relations, Autism Spectrum Disorders, Depression/Suicidality, Clinical encounters)
analysis & modeling of expression of emotions in behavioral (e.g., voice, speech, language, face, body gestures) and physiological signals, and their perception and processing by humans and machines, creation of affect-aware technologies
biosignal sensing and processing of physiological and physical activity, wearable sensing and mobile technologies, understanding mind-body-behavior connections, applications in health, work performance, learning
theory, algorithms and systems: signal processing, information theory, machine learning, pattern recognition, statistical methods, neural network models