Abstract

Sensorineural hearing impairment is associated with increased intraspeech spectral masking and results in degraded speech perception in noisy environment due to increased masking. Speech enhancement using spectral subtraction can be used for suppressing the external noise. Multiband frequency compression of the complex spectral samples has been reported to reduce the effects of increased intraspeech masking. A combination of these techniques is implemented for real-time processing for improving speech perception by persons with moderate sensorineural loss. For reducing computational complexity and memory requirement, spectral subtraction is carried out using a cascaded-median based estimation of the noise spectrum without voice activity detection. Multi-band frequency compression, based on auditory critical bandwidths, is carried out using fixed-frame processing along with least-squares error based signal estimation to reduce the processing delay. To reduce computational complexity the two processing stages share the FFT based analysis-synthesis. The processing is implemented and tested for satisfactory operation, with sampling frequency of 10 kHz, 25.6 ms window with 75% overlap, using a 16-bit fixed-point DSP processor. The real-time operation is achieved with signal delay of approximately 36 ms and using about one-third of the computing capacity of the processor.

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