Speech Enhancement Using Noise Estimation with Adaptive Dynamic Quantile Tracking for Use in Hearing Aids
نویسنده
چکیده
Background noise significantly degrades speech perception for persons with sensorineural hearing impairment. A single-input speech enhancement using adaptive dynamic quantile tracking for estimating the noise spectrum is presented for improving performance of hearing aids. A histogram for each spectral sample is estimated by dynamically tracking ten quantiles and the histogram peak is used as the adaptive quantile for estimating the noise at each spectral sample. It does not involve storage and sorting of past spectral samples for finding the quantiles and thus is suitable for real-time processing. Speech enhancement is carried out using the geometric approach-based spectral subtraction. Speech corrupted with different types of additive stationary and non-stationary noise showed improvement in speech quality to be equivalent to an SNR advantage of 3–6 dB. The algorithmic and computational delays introduced by the processing are acceptable for face-to-face communication.
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