The speech recognition system has been widely used by many researchers using different
methods to fulfill a fast and accurate system. Speech signal recognition is a typical
classification problem, which generally includes two main parts: feature extraction and
classification. In this paper, a new approach to achieve speech recognition task is proposed by
using transformation techniques for feature extraction methods; namely, slantlet transform
(SLT), discrete wavelet transforms (DWT) type Daubechies Db1 and Db4. Furthermore, a
modified artificial neural network (ANN) with dynamic time warping (DTW) algorithm is
developed to train a speech recognition system to be used for classification and recognition
purposes. Twenty three Arabic words were recorded fifteen different times in a studio
by one speaker to form a database. The performance of the proposed system using this
database has been evaluated by computer simulation using MATLAB package. The result
shows recognition accuracy of 65%, 70% and 80% using DWT (Db1), DWT (Db4) and SLT
respectively.
Title: Arabic Manuscript, Concepts and Terms and Their Impact on Determining Its Historical beginnings and extension of its existence.
Researcher: Dr. Atallah Madb Hammadi Zubaie.
Bn the name of Allah Most Merciful
The interest in manuscripts and rules of their investigation and dissemination appeared soon, and the speech in editing terms and concepts appeared in sooner time. When looking at the classified books in the Arab manuscripts , we find the books of the first generation did not allude definition for this term , but rather focused on the importance of manuscripts and their existence locations, indexing, care, and verification rules. The reason for this is that the science of Arabic manuscrip
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