Sub-band adaptive noise reduction algorithm to improve speech intelligibility

doi:10.16511/j.cnki.qhdxxb.2016.26.007

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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%.

Keywords noise reduction sub-band non-linear gains speech intelligibility

ZTFLH:

TN912.35

Issue Date: 15 November 2016

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	LIANG Weiqian
	ZHENG Fang
	ZHENG Jiachun
	PIAO Zhigang

Cite this article:

LIANG Weiqian,ZHENG Fang,ZHENG Jiachun, et al. Sub-band adaptive noise reduction algorithm to improve speech intelligibility[J]. Journal of Tsinghua University(Science and Technology), 2016, 56(11): 1173-1178.

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http://jst.tsinghuajournals.com/EN/10.16511/j.cnki.qhdxxb.2016.26.007 OR http://jst.tsinghuajournals.com/EN/Y2016/V56/I11/1173

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