Sub-band adaptive noise reduction algorithm to improve speech intelligibility

LIANG Weiqian; ZHENG Fang; ZHENG Jiachun; PIAO Zhigang

doi:10.16511/j.cnki.qhdxxb.2016.26.007

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Journal of Tsinghua University(Science and Technology) ›› 2016, Vol. 56 ›› Issue (11) : 1173-1178. DOI: 10.16511/j.cnki.qhdxxb.2016.26.007

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Sub-band adaptive noise reduction algorithm to improve speech intelligibility

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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%.

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

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LIANG Weiqian, ZHENG Fang, ZHENG Jiachun, PIAO Zhigang. Sub-band adaptive noise reduction algorithm to improve speech intelligibility[J]. Journal of Tsinghua University(Science and Technology). 2016, 56(11): 1173-1178 https://doi.org/10.16511/j.cnki.qhdxxb.2016.26.007

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