Scientific mission
Through our research we continue to answer new questions about the nature of the infant cry, while designing and developing efficient signal-processing and machine-learning algorithms for analysis.
Through our research we continue to answer new questions about the nature of the infant cry, while designing and developing efficient signal-processing and machine-learning algorithms for analysis.
We are developing a robust platform for early screening and monitoring of a range of neurological and respiratory conditions affecting infants.
Charles C Onu, Samantha Latremouille, Arsenii Gorin, Junhao Wang, Uchenna Ekwochi, Peter O Ubuane, Omolara A Kehinde, Muhammad A Salisu, Datonye Briggs, Yoshua Bengio, Doina Precup. "A cry for help: Early detection of brain injury in newborns", Preprint arXiv:2310.08338, 2023
Arsenii Gorin, Cem Subakan, Sajjad Abdoli, Junhao Wang, Samantha Latremouille, Charles C. Onu. "Self-supervised learning for infant cry analysis", ICASSP 2023: Self-supervision in Audio, Speech and Beyond Workshop, 2023
Samantha Latremouille, Charles Onu; Junhao Wang; Arsenii Gorin; Wijdan Basfar; Adnan M. Al Ali; Guilherme Sant'Anna. "Acoustic biomarkers of cries from newborns admitted to the NICU with hypoxic ischemic encephalopathy", Abstract and poster presentation at Pediatric Academic Societies meeting on April 27, 2023 in Washington, D.C.
David Budaghyan, Charles C. Onu, Arsenii Gorin, Cem Subakan, Doina Precup. "CryCeleb: A Speaker Verification Dataset Based on Infant Cry Sounds", Preprint arXiv:2305.00969, 2023
Adnan M. Al Ali, Charles Onu, Samantha Latremouille, Wijdan Basfar, Eva B. Senechal, Doina Precup, and Guilherme Sant'Anna. What's wrong, baby? An acoustic analysis of cry triggers in newborns. Abstract and poster presentation at Pediatric Academic Societies meeting on April 22, 2022 in Denver, CO.
CC Onu, J Lebensold, WL Hamilton, D Precup, 20th Annual Conference of the International Speech Communication Association INTERSPEECH 2019.
CC Onu, I Udeogu, E Ndiomu, U Kengni, D Precup, GM Sant'anna, EAD Alikor, P Opara, “Ubenwa: Cry-based Diagnosis of Birth Asphyxia”, Machine Learning for Development workshop, 31st Conference on Neural Information Processing Systems 2017
CC Onu, I Udeogu, E Ndiomu, “SVM Approach to the Cry-based Diagnosis of Birth Asphyxia,” Machine Learning for Healthcare workshop, 29th Conference on Neural Information Processing Systems, 2015. Best Paper Award (Nvidia Titan X GPU)
CC Onu, “Harnessing infant cry for swift, cost-effective diagnosis of perinatal asphyxia in low-resource settings,” IEEE International Humanitarian Technology Conference (IHTC), 2014
We have worked with leading hospitals in Brazil, Canada, and Nigeria.
