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An improved technique for speech signal de-noising based on wavelet threshold and invasive weed optimization algorithm
المؤلفون المشاركون
Abd, Haydar Jabbar
Salim, Nurah
Shaban, Ali
المصدر
Journal of University of Babylon for Engineering Sciences
العدد
المجلد 25، العدد 4 (31 أغسطس/آب 2017)، ص ص. 1413-1423، 11ص.
الناشر
تاريخ النشر
2017-08-31
دولة النشر
العراق
عدد الصفحات
11
التخصصات الرئيسية
الملخص EN
Speech signals play a significant role in the area of digital signal processing.
When these signals pass through air as a channel of propagation, it interacts with noise.
Therefore, it needs removing noise from corrupted signal without altering it.
De-noising is a compromise between the removal of the largest possible amount of noise and the preservation of signal integrity.
To improve the performance of the speech which displays high power fluctuations, a new speech de-noising method based on Invasive Weed Optimization (IWO) is proposed.
In addition, a theoretical model is modified to estimate the value of threshold without any priority of knowledge.
This is done by implementing the IWO algorithm for kurtosis measuring of the residual noise signal to find an optimum threshold value at which the kurtosis function is maximum.
It has been observed that the proposed method appeared better performance than other methods at the same condition.
Moreover, the results show that the proposed IWO algorithm offered a better mean square error(MSE) than Particle Swarm Optimization Algorithm (PSO) for both one and multilevel decomposition.
For instance, IWO brought an improvement in MSE in the range of 0.01 compared with PSO for multilevel decomposition.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Shaban, Ali& Abd, Haydar Jabbar& Salim, Nurah. 2017. An improved technique for speech signal de-noising based on wavelet threshold and invasive weed optimization algorithm. Journal of University of Babylon for Engineering Sciences،Vol. 25, no. 4, pp.1413-1423.
https://search.emarefa.net/detail/BIM-923492
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Shaban, Ali…[et al.]. An improved technique for speech signal de-noising based on wavelet threshold and invasive weed optimization algorithm. Journal of University of Babylon for Engineering Sciences Vol. 25, no. 4 (2017), pp.1413-1423.
https://search.emarefa.net/detail/BIM-923492
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Shaban, Ali& Abd, Haydar Jabbar& Salim, Nurah. An improved technique for speech signal de-noising based on wavelet threshold and invasive weed optimization algorithm. Journal of University of Babylon for Engineering Sciences. 2017. Vol. 25, no. 4, pp.1413-1423.
https://search.emarefa.net/detail/BIM-923492
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Text in English ; abstracts in English and Arabic.
رقم السجل
BIM-923492
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
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