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.
Özet
Tekrarlar, anlamı kuvvetlendirmek, ifadeyi zenginleştirmek amacıyla kullanılan dil unsurlarıdır. Ural Batır destanı da tekrarlar, özellikle de ikilemeler açısından zengindir. Bu yazıda, Ural Batır destanındaki ikilemeler gruplandırılarak verilecek ve değerlendirmesi yapılacaktır.
Anahtar Kelimeler: Tekrar, ikileme, aralıklı ikileme, destan.
Abstract
Word repeating is language items used for strengthen the meaning and riching the expression. By this view, Ural Batır epic is a good example for word repeating units. In this paper, Ural Batır epic’s word repeating has been presented by classification.
Key Words: Repeating, a pair words, a pair words by space, epic.
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