مشاهده مشخصات مقاله
A New Wavelet Thresholding Method for Speech Enhancement Based on Symmetric Kullback-Leibler Divergence
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نویسنده (ها) |
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Shima Tabibian
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Ahmad Akbari
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Babak Nasersharif
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مربوط به کنفرانس |
چهاردهمین کنفرانس بینالمللی سالانه انجمن کامپیوتر ایران |
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چکیده |
Performance of wavelet thresholding methods for
speech enhancement is dependent on estimating an
exact threshold value in the wavelet sub-bands. In this
paper, we propose a new method for more exact
estimating the threshold value. We proposed to
determine the threshold value based on the symmetric
Kullback-Leibler divergence between the probability
distributions of noisy speech and noise wavelet
coefficients. In the next step, we improved this value
using segmental SNR. We used some of TIMIT
utterances to assess the performance of the proposed
threshold. The algorithm is evaluated using the PESQ
score and the SNR improvement. In average, we obtain
2db SNR improvement and a PESQ score increase up
to 0.7 in comparison to the conventional wavelet
thresholding approaches. |
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قیمت |
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برای اعضای سایت : ۱٠٠,٠٠٠ ریال
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برای دانشجویان عضو انجمن : ۲٠,٠٠٠ ریال
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برای اعضای عادی انجمن : ۴٠,٠٠٠ ریال
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