Shrikanth (Shri) Narayanan

University Professor and Niki & Max Nikias Chair in Engineering
Professor of Electrical & Computer Engineering
Professor of Computer Science, Linguistics, Psychology, Neuroscience, Pediatrics, Otolaryngology-Head & Neck Surgery

Research Topics

  1. Research in the Signal Analysis and Interpretation Laboratory is devoted to theoretical issues and practical applications of:
  2. Speech and Language Processing & Automatic Speech Recognition
  3. Speech Production Modeling, Articulatory Acoustics, Speech Synthesis
  4. Human Emotion Modeling; Affective computing
  5. Behavioral Signal Processing and Behavioral Informatics
  6. Biomedical Signal Processing and Modeling; Imaging & Instrumentation for Speech Research
  7. Human Machine Interaction; Multimodal-Multimedia Interfaces, Devices, and Systems

Research Overview

SAIL conducts fundamental and applied research in human-centered information processing. Our emphasis is on speech, audio, language, biomedical and multi-modal signal processing, machine learning and pattern recognition.

SAIL's research applications and systems development especially focus on domains with direct societal relevance including in human health and well being (both basic and translational research such as in the domains of autism, pediatric obesity and disordered speech production), education (technologies for literacy and language learning) and defense (signal and pattern classification, speech recognition and translation, virtual human-based systems and audio-visual scene analysis). SAIL Alumni occupy important positions in both academia and industry

SAIL supports a collaborative interdisciplinary environment and bridges research from several departments and schools both within and outside USC.

Research is supported by grants from NSF, NIH, DARPA, Army, ONR, DHS, and foundations including Autism Speaks, Simons, and Nancy Lurie Marks Family Foundation, as well as industry support.

Selected Publications

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 Full list:

Christina Hagedorn, Michael Proctor, Louis Goldstein, Stephen M. Wilson, Bruce Miller, Maria Luisa Gorno Tempini, Shrikanth Narayanan. Characterizing Articulation in Apraxic Speech Using Real-time Magnetic Resonance Imaging. Journal of Speech, Language, and Hearing Research. 2016

Tanaya Guha, Zhaojun Yang, Ruth Grossman and Shrikanth Narayanan. A Computational Study of Expressive Facial Dynamics in Children with Autism. IEEE Transactions on Affective Computing. 2016

Armen Arevian, Daniel Bone, Nikolaos Malandrakis, Victor R Martinez, Kenneth B Wells, David J Miklowitz, Shrikanth Narayanan. Clinical state tracking in serious mental illness through computational analysis of speech. PLoS ONE. 15(1): e0225695, 2020

Daniel Bone, Somer Bishop, Matthew P. Black, Matthew S. Goodwin, Catherine Lord, Shrikanth S. Narayanan. Use of Machine Learning to Improve Autism Screening and Diagnostic Instruments: Effectiveness, Efficiency, and Multi-Instrument Fusion. Journal of Child Psychology and Psychiatry. 2016

James Gibson, Athanasios Katsamanis, Francisco Romero, Bo Xiao, Panayiotis Georgiou, Shrikanth Narayanan. Multiple Instance Learning for Behavioral Coding.  IEEE Transactions on Affective Computing, 2016

Bo Xiao,  Zac Imel, Panayiotis Georgiou, David Atkins and Shrikanth Narayanan."Rate my therapist":  Automated detection of empathy in drug and alcohol counseling via speech and language processing. PLoS ONE, 10(12): e0143055. 2015

Maarten Van Segbroeck, Allison Knoll, Pat Levitt, Shrikanth Narayanan. MUPET - Mouse Ultrasonic Profile ExTraction: A signal processing tool for rapid and unsupervised analysis of ultrasonic vocalizations. Neuron. 94: 465–485,  March  2017 

Sajan Lingala, Yinghua Zhu, Yoon-Chul Kim, Asterios Toutios, Shrikanth Narayanan, Krishna Nayak. A fast and flexible MRI system for the study of dynamic vocal tract shaping. Magnetic Resonance in Medicine. 2016

Theodora Chaspari, Andreas Tsiartas, Leah I. Stein, Sharon A. Cermak, and Shrikanth S. Narayanan. Sparse Representation of Electrodermal Activity with Knowledge-Driven Dictionaries. IEEE Transactions on Biomedical Engineering.  62(3): 960-971, March 2015

Daniel Bone, Matthew S. Goodwin, Matthew P. Black, Chi-Chun Lee, Kartik Audhkhasi, and Shrikanth Narayanan. Applying Machine Learning to Facilitate Autism Diagnostics:  Pitfalls and promises. Journal of Autism and Developmental Disorders. 45(5), 1121-1136, 2015

Vikram Ramanarayanan, Adam Lammert, Louis Goldstein and Shrikanth Narayanan. Are articulatory settings mechanically advantageous for speech motor control? PLoS ONE, 9(8): e104168. doi:10.1371/journal.pone.0104168, 2014