Abstract: This workshop will provide hands-on experience with computational approaches for modeling normal and impaired auditory peripheral processing. The session will begin with an overview of auditory peripheral function and current modeling strategies, followed by an interactive component using Jupyter notebooks that will enable participants to generate their own simulations of auditory processing. Some familiarity with the biology of hearing is helpful but not required, and no prior coding experience is necessary.

Biography: Annesya is a 5th-year PhD candidate in the Speech and Hearing Bioscience and Technology program at Harvard University, where her research focuses on computational modeling of cochlear implant–mediated auditory perception. Her long-term research goal is to use machine learning models for developing better cochlear implants. Before joining her PhD, she graduated with a Bachelor of Engineering from Jadavpur University, India, specializing in signal processing and machine learning, where she worked on drone-based sound source localization and acoustic array systems for medical and humanitarian applications. During her time as a research scientist intern at Meta Reality Labs, she also developed machine learning models for reference-free SNR prediction and for perceptually guided evaluation of generated speech and contributed to evaluation algorithms underlying Meta’s Conversation Focus technology in smart glasses.