Minimize Frequency Overlapping of Auditory Signals using Complementary Comb Filters
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Abstract
Cochlear hearing impairment causes overlapping of auditory speech signals having close frequency contents. Such impairment arises due to the hardening of hearing cells that effects the frequency-splitting ability of inner ear. Person with such disabilities are unable to distinguish between speech signals with high-frequency correlation. This work proposes an implementation of complementary feedforward comb filters to reduce the overlapping of auditory signals. In auditory frequency overlapping, a lower frequency loses their identities due to presence of higher frequencies. Here, two complementary comb filters have been designed to match alternate critical bandwidths of audio signals. Results shown that presenting these alternate frequency bands to human ear in the even-odd index significantly minimizes the frequency overlapping and thereby improves audibility in the hearing impaired.
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How to Cite
Divekar, S., & Nigam, M. (2022). Minimize Frequency Overlapping of Auditory Signals using Complementary Comb Filters. SAMRIDDHI : A Journal of Physical Sciences, Engineering and Technology, 14(03), 333-336. https://doi.org/10.18090/samriddhi.v14i03.13
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Research Article
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
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Analysis”, IEEE Transactions on Biomedical Engineering,
Volume: 67, Issue: 11, pp. 3253 – 3261, Nov. 2020.
[2] Luca Remaggi; Philip J. B. Jackson; Wenwu Wang, “Modeling
the Comb Filter E ect and Interaural Coherence for Binaural
Source Separation”, IEEE/ACM Transactions on Audio, Speech,
and Language Processing, Volume: 27, Issue: 12, pp. 2263 – 2277,
Dec. 2019.
[3] Jonathan S. Abel; Elliot K. Canfield-Dafilou, “Dispersive
Delay and Comb Filters Using a Modal Structure”, IEEE Signal
Processing Letters, Volume: 26, Issue: 12, pp. 1748 – 1752, Dec.
2019.
[4] Valerie Hanson, Kofi Odame, “ Real-Time Embedded
Implementation of the Binary Mask Algorithm for Hearing
Prosthetics”, IEEE Transactions on Biomedical Circuits and
Systems, Vol. 8, No.4, August 2014.
[5] Tao Zhang, Fred Mustiere, Christophe Micheyl, “Intelligent
hearing aids: The next revolution”, 38th Annual International
Conference of the IEEE Engineering in Medicine and Biology
Society (EMBC), Orlando, FL, USA, 16-20 Aug. 2016.
[6] L. Lightburn, E. D. Sena, A. Moore, P. A. Naylor, M. Brookes,
“Improving the perceptual quality of ideal binary masked
speech”, Proc. Int. Conf. Acoust. Speech Signal Process, pp.
661-665, 2017.
[7] D. S. Williamson, D. L. Wang, “Time-frequency masking
in the complex domain for speech dereverberation and
denoising”, IEEE/ACM Transaction on Audio Speech Lang.
Process., vol. 25, no. 7, pp. 1492-1501, Jul. 2017.
[8] Yuma Koizumi, Kenta Niwa, Yusuke Hioka, Kazunori Kobayashi,
Yoichi Haneda, “DNN-Based Source Enhancement to Increase
Objective Sound Quality Assessment Score”, IEEE Transactions
on Audio Speech and Language Processing, vol. 26, no. 10, pp.
1780-1792, 2018.
[9] Huan Hu; Stojan Radic, “Sub-Nyquist Ultra-Wideband Sparse
Signal Reception via Variable Frequency Comb”, Journal of
Lightwave Technology, pp. 4625 – 4631, Vol: 38, Issue: 17, Sept
2020.
[10] Anil Nagathil; Claus Weihs; Rainer Martin, “Spectral Complexity
Reduction of Music Signals for Mitigating E ects of Cochlear
Hearing Loss”, IEEE/ACM Transactions on Audio, Speech, and
Language Processing, Volume: 24, Issue: 3, pp. 445 – 458,
March 2016.
[11] Sandeep Kolluri et al. “A New Control Architecture With Spatial
Comb Filter and Spatial Repetitive Controller for Circulating
Current Harmonics Elimination in a Droop-Regulated
Modular Multilevel Converter for Wind Farm Application”, IEEE
Transactions on Power Electronics, Vol. 34, Issue: 11, pp. 10509 –
10523, Nov. 2019.
[12] Nalluri, S. K., & Parasaram, V. K. B. (2015). Automating
Software Builds with Jenkins: Design Patterns and Failure
Handling. International Journal of Technology, Management
and Humanities, 1(01), 16-33.
https://doi.org/10.21590/ijtmh.01.02.03
[13] Wang Xia; Jiang Hao; Liang Ruiyu; Wang Qingyun; Zhao Li; Zou
Cairong, “An Integrated Frequency Lowering Algorithm for
Sensorineural Hearing Impairment”, IEEE Eighth International
Conference on Measuring Technology and Mechatronics
Automation (ICMTMA), Macau, China, 11-12 March 2016.
[14] Thijs van de Laar; Bert de Vries, “A Probabilistic Modeling
Approach to Hearing Loss Compensation”, IEEE/ACM
Transactions on Audio, Speech, and Language Processing,
Volume: 24, Issue: 11, pp. 2200 – 2213, Nov. 2016.