Open Access

ARTICLE

Research on Nonlinear Frequency Compression Method of Hearing Aid with Adaptive Compression Ratio

Xia Wang¹, Hongming Shen¹, Huawei Tao², Ruiyu Liang³, Xing Deng^4,5, Haijian Shao⁵, Li Zhao^6,*, Cairong Zou⁶

1 School of Information Science and Technology, Nantong University, Nantong, 226019, China.
2 School of Information Science and Engineering, Henan University of Technology, Zhengzhou, 450001, China.
3 School of Communication Engineering, Nanjing Institute of Technology, Nanjing, 211167, China.
4 School of Automation, Key Laboratory of Measurement and Control for CSE, Ministry of Education, Southeast University, Nanjing, 210096, China.
5 School of Computer Science, Jiangsu University of Science and Technology, Zhenjiang, 212003, China.
6 School of Information Science and Engineering, Southeast University, Nanjing, 210096, China.

* Corresponding Author: Li Zhao. Email: .

Computer Modeling in Engineering & Sciences 2019, 121(2), 551-567. https://doi.org/10.32604/cmes.2019.06314

Abstract

To make full use of the residual audible frequency band of hearing-loss patients and improve the intelligibility of speech, an adaptive nonlinear frequency compression (NFC) algorithm is proposed, which amplifies signals below the cutoff frequency while compresses signals above the cutoff frequency. Firstly, high-frequency signals are decomposed to critical band signals according to the BARK scale. Secondly, the global compression ratio is determined according to the patient's cutoff frequency and maximum audible frequency. Thirdly, the sub-band compression ratio is adaptively determined based on the global compression ratio and normalized average energy of subband signals. Finally, the high frequency signals are transposed to low frequency bands by compression mapping, and the phases are adjusted to the same as the original low frequency signals. Experimental results of speech intelligibility with nine subjects demonstrate that compared to conventional amplitude amplification and nonlinear frequency compression algorithms the proposed algorithm significantly improves the intelligibility of initials and sentences, while not affects the intelligibility of finals and tones significantly.

---

Keywords

---