كبس ملفات الكلام وتشفيرها باستخدام الشبكة العصبية ذات الانتشار العكسي

Abstract

AbstractSpeech compression is a very important field of internet application or to transfer through network and telecommunication. This research studies speech compression using neural network, which is commonly used with images files compression. It has been focused on the files that include speech only and do not contain other sounds like music or car sound, or animal sound etc. In this research it has been used Back Propagation Neural Network BPNN for speech signals compression. Several experiments have been performed which differ in configuration of data that entered to the network. The highest compression ratio obtained is (1:10) from the original data. The compression files obtained represent as encipher files because they have little data with compared to original file, and also they night be not useful if it has been stolen through transmitting operation on the network, they be able to be decompressed to the original without their weights matrix can not, so the promising benefit from this compression is to achieve double aims. Speech security is an important goal for users of many speech communication systems. To obtain a desired level of security an encryption scheme should be added for speech signal before transmission.