Cochlear Implant Research Lab (CIRLab)
The mission of the Cochlear Implant Research Lab (CIRLab) is to improve the quality of life for individuals with cochlear implants and more broadly, those with hearing loss.
About the Lab
Cochlear implants are among the most successful neural prosthetic devices, restoring access to sound for more than a million people with severe-to-profound deafness. However, despite substantial gains in speech intelligibility in quiet settings, cochlear implant users continue to face significant challenges in noisy environments—the conditions that define most real-world listening.
Our research therefore focuses on understanding how people navigate everyday listening situations, particularly in noise, and leveraging that knowledge to advance sound coding and signal processing strategies for cochlear implants.
Lab Members
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Publications
- 2025. Borjigin A., Dennison S. R., Kan A., Litovsky R. Y. Localization performance of cochlear implant users with a real-time bilaterally-synchronized sound coding strategy that provides explicit interaural timing cues with mixed rates of stimulation. [Frontiers in Neuroscience] 19:1682452. doi: https://doi.org/10.3389/fnins.2025.1682452
- 2025. Borjigin A., Bharadwaj H. M. Individual Differences Elucidate the Perceptual Benefits Associated with Robust Temporal Fine-Structure Processing. [PNAS] 122 (1) e2317152121, doi: https://doi.org/10.1073/pnas.2317152121
- 2024. Borjigin A., Kokkinakis K., Bharadwaj H. M., Stohl J. S. Deep Learning Restores Speech Intelligibility in Multi-Talker Interference for Cochlear Implant Users. [Nature Scientific Reports] 14, Article number: 13241, doi: https://doi.org/10.1038/s41598-024-63675-8
- 2024. Borjigin A., Bakst S., Anderson K., Litovsky R. Y., Niziolek, C.A. Discrimination and Sensorimotor Adaptation of Self-Produced Vowels in Cochlear Implant Users. [JASA] 155, 1895–1908, doi: https://doi.org/10.1121/10.0025063
- 2023. Mok B. A., Viswanathan V., Borjigin A., Singh R., Kafi H., Bharadwaj H. M. Web-based Psychoacoustics: Hearing Screening, Infrastructure, and Validation. [Behavior Research Methods] 56, 1433–1448, doi: https://doi.org/10.3758/s13428-023-02101-9
- 2022. Borjigin A., Alexandra R. M., Bharadwaj H. M. Individualized Assays of Temporal Coding in the Ascending Human Auditory System. [eNeuro], 9 (2), 0378-21, doi: https://doi.org/10.1523/ENEURO.0378-21.2022
About Our Research
Bringing Back the Missing Details of Sound
Many people with cochlear implants can understand speech in quiet, but still struggle in real-world situations—like finding where a sound is coming from, enjoying music, following conversations in echoey rooms, or keeping up without feeling exhausted. Our research focuses on a key piece of sound that today’s cochlear implants largely leave out: temporal fine structure (TFS).
When sound reaches the ear, it has two parts: a slow “envelope” that carries intensity or loudness changes, and fast, rapid timing (or frequency) information called temporal fine structure. TFS helps the brain perceive pitch, locate sounds in space, make sense of speech in reverberant rooms, and manage listening effort. Most current cochlear implant strategies do not encode these fast timing cues well—meaning an important layer of sound is missing.
This project is to test whether adding TFS back into cochlear implant processing can improve four areas that are important for everyday hearing:
- Spatial hearing – knowing where sounds are coming from
- Pitch perception & music appreciation – hearing melodies and vocal emotion
- Listening in reverberation – understanding speech in echoey spaces
- Listening effort – how hard the brain has to work to follow sound
CI users will complete listening tasks with and without TFS-based processing, while we measure both performance and effort using behavioral and physiological tools.
Our goal is to build a clearer picture of how restoring these missing timing cues can make hearing feel more natural, less tiring, and more connected to the world.
Artificial Intelligence & Hearing
Everyday listening is full of challenges—background noise, overlapping voices, and fast-changing sound environments. For people with hearing loss and cochlear implants, these challenges can make communication exhausting and frustrating.
Our lab uses artificial intelligence (AI) to teach computers how to “listen” the way humans do, so they can improve sound before it reaches the ear or a cochlear implant. We design deep-learning systems that automatically separate speech from noise, enhance important sound features, and adapt to different listening environments in real time. By combining AI with hearing science, our goal is to make speech clearer, reduce listening effort, and improve communication in the real world—whether in a busy restaurant, a classroom, or at home.
Deep Neural Network (DNN)–Based Noise Reduction for Cochlear Implants
Background noise is one of the biggest barriers to understanding speech with a cochlear implant. Traditional noise-reduction methods rely on simple rules and often fail in complex, real-world environments. Our lab develops deep neural networks (DNNs) trained on large collections of real-world sounds to learn how to separate speech from noise. These AI models can recognize patterns that traditional algorithms miss and can clean up the signal before it enters the cochlear implant. This work aims to:
- Improve speech clarity in noisy environments
- Preserve important sound cues for natural listening
- Reduce mental effort during conversation
Predicting Cochlear Implant Outcomes with Machine Learning & Big Data
Cochlear implant outcomes vary widely—some people hear very well after implantation, while others continue to struggle. Currently, clinicians have limited tools to predict who will benefit most from a cochlear implant before surgery. We are developing machine-learning models that analyze large clinical datasets to uncover patterns linking pre-operative factors (such as hearing history and test results) to post-implant outcomes. Our goal is to create a clinical decision-support tool that can:
- Estimate likely hearing outcomes before surgery
- Help set realistic expectations for patients and families
- Support clinicians in personalizing treatment and rehabilitation
Our goal is to ultimately make everyday communication easier and less tiring for CI users, and make cochlear implant care more precise, personalized, and transparent.
Contact Us
Behavioral Science Building
390 S 1530 E, BEH SCI
Room 1210
Salt Lake City, UT 84112