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Noise reduction using wavelet thresholding of multitaper estimators and geometric approach to spectral subtraction for speech coding strategy.

Chu KC, Choi CT - Clin Exp Otorhinolaryngol (2012)

Bottom Line: 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 included 25 Mandarin sentences as test materials.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.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science and Institute of Biomedical Engineering, National Chiao Tung University, Taiwan.

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.

No MeSH data available.


HiRes 120 vocoder with noise reduction process.
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Figure 1: HiRes 120 vocoder with noise reduction process.

Mentions: This study used a HiRes 120 strategy (8) together with a noise reduction process (Fig. 1) as the speech coding strategy or vocoder. All the test materials were processed as the input sound of the vocoder and total of 600 sound outputs were generated (300 input sounds×2 noise reduction methods). The sound outputs were then measured by the PESQ (Figs. 1-3) to evaluate the sound quality.


Noise reduction using wavelet thresholding of multitaper estimators and geometric approach to spectral subtraction for speech coding strategy.

Chu KC, Choi CT - Clin Exp Otorhinolaryngol (2012)

HiRes 120 vocoder with noise reduction process.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3369986&req=5

Figure 1: HiRes 120 vocoder with noise reduction process.
Mentions: This study used a HiRes 120 strategy (8) together with a noise reduction process (Fig. 1) as the speech coding strategy or vocoder. All the test materials were processed as the input sound of the vocoder and total of 600 sound outputs were generated (300 input sounds×2 noise reduction methods). The sound outputs were then measured by the PESQ (Figs. 1-3) to evaluate the sound quality.

Bottom Line: 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 included 25 Mandarin sentences as test materials.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.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science and Institute of Biomedical Engineering, National Chiao Tung University, Taiwan.

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.

No MeSH data available.