1. Key Laboratory of Maritime Communication and Intelligent Electronic Systems of Fujian Province, College of Information Engineering, Jimei University, Xiamen 361021, China;
2. Center for Speech and Language Technologies, Research Institute of Information Technology, Tsinghua University, Beijing 100084, China;
3. Xiamen LA and Associates Medical Equipment Co., Ltd., Xiamen 361009, China
Abstract：Noise reduction algorithms to improve speech intelligibility are needed when sounds are compressed and amplified in hearing aids. A sub-band adaptive noise reduction algorithm was developed with a weighted overlap-add filter bank and psycho-acoustic model for the sub-band splitting. The non-linear noise reduction gains are computed with an estimated a posteriori signal to noise ratio (SNR) and an a priori SNR. The gain floors are determined based on the estimated noise level expressed as the dB sound pressure level (SPL). The final gains are smoothed between the frames by a peak detector with carefully selected attack and release time constants. Listening tests show 12% to 45% improvements in intelligibility by this algorithm for noise corrupted speech. A quantified gain table is also used to replace the non-linear gain computing when the algorithm is implemented on the EZAIRO5900 digital signal processor, with the execution cycle reduced by about 30%.
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