Arabic Word Speaker Identification using Fuzzy Wavelet Neural Network

نویسنده

  • Dhiadeen SALIH
چکیده

In this paper, an automatic text–independent Arabic word speaker identification system is presented using Fuzzy Wavelet Neural Network terminology (FWNN). The approach is combining wavelet theory to fuzzy logic and neural network which lead to fabricate a Fuzzy Wavenet . Position and dilation of the fuzzy wavenets are fixed and the weights are optimized according to learning algorithm in the network. The feature extraction for real Arabic word signals through Discrete Wavelet Transform (DWT) model is used. The proposed terminology here is training process for some words of all speakers done in FWNN learning phase then test for the other sample speech signals for speakers have been used in FWNN classification phase. Success theory of fuzzy wavenets has been generalized by extension to biorthogonal wavelets which lead to identification system development . Results showing the effectiveness of the proposed system presented in this paper.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Discrete Wavelet Transform & Linear Prediction Coding Based Method for Speech Recognition via Neural Network

In the proposed work, the techniques of wavelet transform (WT) and neural network were introduced for speech based text-independent speaker identification and Arabic vowel recognition. The linear prediction coding coefficients (LPCC) of discrete wavelet transform (DWT) upon level 3 features extraction method was developed. Feature vector fed to probabilistic neural networks (PNN) for classifica...

متن کامل

Forecasting Stock Market Using Wavelet Transforms and Neural Networks: An integrated system based on Fuzzy Genetic algorithm (Case study of price index of Tehran Stock Exchange)

The jamor purpose of the present research is to predict the total stock market index of Tehran Stock Exchange, using a combined method of Wavelet transforms, Fuzzy genetics, and neural network in order to predict the active participations of finance market as well as macro decision makers.To do so, first the prediction was made by neural network, then a series of price index was decomposed by w...

متن کامل

Speaker Identification System Using Wavelet Transformation and Neural Network

In this Present study, the technique of wavelet transform and neural network were developed for speech based text-dependent and text0independent speaker identification. 390 feature were fed to feed-forward back propagation neural network for classification The function of feature extraction and classification are performed using wavelet and neural network system. The declared result shows that ...

متن کامل

The use of wavelet - artificial neural network and adaptive neuro fuzzy inference system models to predict monthly precipitation

Precipitation forecasting due to its random nature in space and time always faced with many problems and this uncertainty reduces the validity of the forecasting model. Nowadays nonlinear networks as intelligent systems to predict such complex phenomena are widely used. One of the methods that have been considered in recent years in the fields of hydrology is use of wavelet transform as a moder...

متن کامل

The Use of Wavelets in Speaker Feature Tracking Identification System Using Neural Network

Continuous and Discrete Wavelet Transform (WT) are used to create text-dependent robust to noise speaker recognition system. In this paper we investigate the accuracy of identification the speaker identity in nonstationary signals. Three methods are used to extract the essential speaker features based on Continuous, Discrete Wavelet Transform and Power Spectrum Density (PSD). To have better ide...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2009