文件名称:noise_reduction_technique
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duction techniques proposed in the art are expressed as a spectral
gain depending on the a priori SNR. In the well-known decision-
directed approach, the a priori SNR depends on the speech spec-
trum estimation in the previous fr a me. As a consequence the gain
function matches the previous fr a me rather than the current one
which degrades the noise reduction performance. We propose a
new method called Two-Step Noise Reduction (TSNR) technique
which solves this problem while maintaining the benefi ts of the
decision-directed approach. This method is analyzed and results
in voice communication and speech recognition context are given.-noise estimate
gain depending on the a priori SNR. In the well-known decision-
directed approach, the a priori SNR depends on the speech spec-
trum estimation in the previous fr a me. As a consequence the gain
function matches the previous fr a me rather than the current one
which degrades the noise reduction performance. We propose a
new method called Two-Step Noise Reduction (TSNR) technique
which solves this problem while maintaining the benefi ts of the
decision-directed approach. This method is analyzed and results
in voice communication and speech recognition context are given.-noise estimate
相关搜索: TSNR
decision
directed
synchronization
noise
estimation
Noise
Reduction
noise
noise_reduction_technique
decision
directed
synchronization
noise
estimation
Noise
Reduction
noise
noise_reduction_technique
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A two-step noise reduction technique.pdf