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Development of a Real Time Sparse Non-Negative Matrix Factorization Module for Cochlear Implants by Using xPC Target
Institute of Sound and Vibration Research, University of Southampton, Southampton SO17 1BJ, UK
Department of Mechanical Engineering, Jiangsu University, Zhenjiang 212013, China
Medical Physics, University of Oldenburg and Cluster of Excellence Hearing4all 26129, Germany
School of Informatics, University of Edinburgh, Edinburgh EH8 9AB, UK
* Author to whom correspondence should be addressed.
Received: 19 July 2013; in revised form: 9 September 2013 / Accepted: 26 September 2013 / Published: 14 October 2013
Abstract: Cochlear implants (CIs) require efficient speech processing to maximize information transmission to the brain, especially in noise. A novel CI processing strategy was proposed in our previous studies, in which sparsity-constrained non-negative matrix factorization (NMF) was applied to the envelope matrix in order to improve the CI performance in noisy environments. It showed that the algorithm needs to be adaptive, rather than fixed, in order to adjust to acoustical conditions and individual characteristics. Here, we explore the benefit of a system that allows the user to adjust the signal processing in real time according to their individual listening needs and their individual hearing capabilities. In this system, which is based on MATLABR , SIMULINKR and the xPC TargetTM environment, the input/outupt (I/O) boards are interfaced between the SIMULINK blocks and the CI stimulation system, such that the output can be controlled successfully in the manner of a hardware-in-the-loop (HIL) simulation, hence offering a convenient way to implement a real time signal processing module that does not require any low level language. The sparsity constrained parameter of the algorithm was adapted online subjectively during an experiment with normal-hearing subjects and noise vocoded speech simulation. Results show that subjects chose different parameter values according to their own intelligibility preferences, indicating that adaptive real time algorithms are beneficial to fully explore subjective preferences. We conclude that the adaptive real time systems are beneficial for the experimental design, and such systems allow one to conduct psychophysical experiments with high ecological validity.
Keywords: cochlear implants; non-negative matrix factorization; speech enhancement; vocoder; xPC Target; real-time system
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MDPI and ACS Style
Hu, H.; Krasoulis, A.; Lutman, M.; Bleeck, S. Development of a Real Time Sparse Non-Negative Matrix Factorization Module for Cochlear Implants by Using xPC Target. Sensors 2013, 13, 13861-13878.
Hu H, Krasoulis A, Lutman M, Bleeck S. Development of a Real Time Sparse Non-Negative Matrix Factorization Module for Cochlear Implants by Using xPC Target. Sensors. 2013; 13(10):13861-13878.
Hu, Hongmei; Krasoulis, Agamemnon; Lutman, Mark; Bleeck, Stefan. 2013. "Development of a Real Time Sparse Non-Negative Matrix Factorization Module for Cochlear Implants by Using xPC Target." Sensors 13, no. 10: 13861-13878.