Clin Exp Otorhinolaryngol.  2012 Apr;5(Suppl 1):S65-S68.

Noise Reduction Using Wavelet Thresholding of Multitaper Estimators and Geometric Approach to Spectral Subtraction for Speech Coding Strategy

• Chu KC
• Choi CT

Abstract

OBJECTIVES
Noise reduction using wavelet thresholding of multitaper estimators (WTME) and geometric approach to spectral subtraction (GASS) can improve speech quality of noisy sound for speech coding strategy. This study used Perceptual Evaluation of Speech Quality (PESQ) to assess the performance of the WTME and GASS for speech coding strategy.
METHODS
This study included 25 Mandarin sentences as test materials. Environmental noises including the air-conditioner, cafeteria and multi-talker were artificially added to test materials at signal to noise ratio (SNR) of -5, 0, 5, and 10 dB. HiRes 120 vocoder WTME and GASS noise reduction process were used in this study to generate sound outputs. The sound outputs were measured by the PESQ to evaluate sound quality.
RESULTS
Two figures and three tables were used to assess the speech quality of the sound output of the WTME and GASS.
CONCLUSION
There is no significant difference between the overall performance of sound quality in both methods, but the geometric approach to spectral subtraction method is slightly better than the wavelet thresholding of multitaper estimators.

Keyword

Cochlear implant; Speech production measurement

MeSH Terms

Clinical Coding
Cochlear Implants
Noise
Signal-To-Noise Ratio
Speech Production Measurement

Figure

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  Fig. 1 HiRes 120 vocoder with noise reduction process.

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  Fig. 2 Structure of perceptual evaluation of speech quality model (6).

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  Fig. 3 Perceptual Evaluation of Speech Quality (PESQ) evaluation method for testing quality with environmental noise (7).

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  Fig. 4 The mean value of each signal to noise ratio (SNR) based on difference background environment.

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  Fig. 5 The overall mean value of each signal to noise ratio (SNR).

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