MRC Cognition and Brain Sciences Unit
Tobias.Goehring@mrc-cbu.cam.ac.uk
01223 769486
MRC Fellow and Senior Research Associate
My goal is to help in restoring the sense of sound by improving hearing devices for people with hearing difficulties.
I am establishing the Deep Hearing Lab at the CBU embedded in the Cambridge Hearing Group. Our research is focused on speech perception with hearing devices (cochlear implants, hearing aids and hearables) using techniques from auditory neuroscience, engineering and deep learning. The goal is to increase scientific understanding and to inspire improvements to future devices and clinical insights. An important aspect is the direct evaluation with people to measure listening benefits and perceptual effects.
I hold a 5-year Fellowship (MRC Career Development Award) since summer 2020 and am PI on Grants by The Evelyn Trust and the Wellcome Trust ISSF, the Newton Trust and the University of Cambridge (Joint Research Grant Scheme) as well as Supervisor on a Fellowship by the Fondation pour L'audition to Dr Clement Gaultier. I earned my PhD as an EU Marie Curie Fellow (www.icanhear.eu) at the University of Southampton supervised by Stefan Bleeck, and worked as Post-doc with Bob Carlyon, Brian CJ Moore and Jessica Monaghan. Before coming to Cambridge, I was a visiting researcher at Macquarie University in Australia and worked as R&D engineer in the Automotive Industry in Germany for 2 years. I studied Electrical Engineering at TU Braunschweig in Germany and completed internships at headphone (Sennheiser) and medical device manufacturers (Dräger Medical). I am passionate about technology, acoustics and medical applications all of which unite in my research on hearing devices.
You can find more information and access to my publications here:
We rely on volunteers to take part in our listening studies. If you are using hearing devices and interested, please get in touch!
ARCHER-BOYD, A.W., HARLAND, A., GOEHRING, T. , CARLYON, R.P. (2023) An online implementation of a measure of spectro-temporal processing by cochlear-implant listeners, JASA Express Letters, 3, 014402 [Open Access]
GARCIA, C., DEEKS, J., GOEHRING, T. , Borsetto, D., Bance, M., CARLYLON, R.P. (2022) SpeedCAP: An Efficient Method for Estimating Neural Activation Patterns Using Electrically Evoked Compound Action-Potentials in Cochlear Implant Users, Ear and Hearing, 10.1097/AUD.0000000000001305 [Open Access]
Brochier, T., Schlittenlacher, J., Roberts, I., GOEHRING, T. , Jiang, C., Vickers, D., Bance, M. (2022) From Microphone to Phoneme: An End-to-End Computational Neural Model for Predicting Speech Perception with Cochlear Implants, IEEE Transactions on Biomedical Engineering, 13 Apr 2022, PP [Open Access]
CARLYON, R.P., GOEHRING, T. (2021) Cochlear Implant Research and Development in the Twenty-first Century: A Critical Update., Journal of the Association for Research in Otolaryngology : JARO, 22(5):481-508 [Open Access]
GOEHRING, T. , ARCHER-BOYD, A.W., Arenberg, J.G., CARLYON, R.P. (2021) The effect of increased channel interaction on speech perception with cochlear implants, Scientific Reports, 17 May 2021, 11(1):10383 [Open Access]
GARCIA, C., GOEHRING, T. , COSENTINO, S., Turner, R.E., DEEKS, J.M., Brochier, K., Rughooputh, T., Bance, M., CARLYLON, R.P. (2021) The Panoramic ECAP Method: Estimating Patient‑Specifc Patterns of Current Spread and Neural Health in Cochlear Implant Users, The Journal of the Association for Research in Otolaryngology, 22(5):567-589 [Open Access]
Jiang, C., Singhal, S., Landry, T., Roberts, I.V., de Rijk, S.R., Brochier, T., Goehring, T. , Tam, Y.C., CARLYLON, R.P., Malliaraas, G.G., and Bance, M.L. (2021) An Instrumented Cochlea Model for the Evaluation of Cochlear Implant Electrical Stimulus Spread, IEEE Transactions on Bio-medical Engineering,68(7):2281-2288 [Open Access]
ARCHER-BOYD, A., GOEHRING, T. , CARLYON, R. (2020) The effect of free-field presentation and processing strategy on a measure of spectro-temporal processing by cochlear-implant listeners, Trends in Hearing, Jan-Dec 2020;24:2331216520964281 [Open Access]
GOEHRING, T. , Arenberg, J.G., CARLYON, R. (2020) Using Spectral Blurring to Assess Effects of Channel Interaction on Speech-In-Noise Perception with Cochlear Implants, Journal of the Association for Research in Otolaryngology, 21(4):353-371 [Open Access]
LAMPING, W., GOEHRING, T. , Marozeaua, J., CARLYON, R. (2020) The effect of a coding strategy that removes temporally masked pulses on speech perception by cochlear implant users, Hearing Research, 391:107969 [Open Access]
Keshavarzi, M., GOEHRING, T. , Turner, R., Moore, B. (2020) Comparison of effects on subjective intelligibility and quality of speech in babble for two algorithms: A deep recurrent neural network and spectral subtraction, The Journal of the Acoustical Society of America, 145(3):1493 [Open Access]
Fletcher, F., Hadeedi, A. GOEHRING, T. , Mills, S. (2019) Electro-haptic enhancement of speech-in-noise performance in cochlear implant users, Scientific Reports, 9(1):11428 [Open Access]
GOEHRING, T. , ARCHER-BOYD, A., DEEKS, J.M., Arenberg, J.G., CARLYON, R.P. (2019) A Site-Selection Strategy Based on Polarity Sensitivity for Cochlear Implants: Effects on Spectro-Temporal Resolution and Speech Perception, Journal of the Association for Research in Otolaryngology : Jaro, 20(4):431-448 [Open Access]
GOEHRING, T. , Keshavarzi, M., CARLYON, R., Moore, B. (2019) Using recurrent neural networks to improve the perception of speech in non-stationary noise by people with cochlear implants., The Journal of the Acoustical Society of America, 146(1):705 [Open Access]
Fletcher, M.D., Mills, S.R., GOEHRING, T. (2018) Vibro-Tactile Enhancement of Speech Intelligibility in Multi-talker Noise for Simulated Cochlear Implant Listening., Trends in Hearing, 22:2331216518797838 [Open Access]
Keshavarzi, M., GOEHRING, T. , Zakis, J., Turner, R.E., Moore, B.C.J (2018) Use of a Deep Recurrent Neural Network to Reduce Wind Noise: Effects on Judged Speech Intelligibility and Sound Quality, Trends in Hearing, 01 Jan 2018, 22:2331216518770964 [Open Access]
