A New Step in Arabic Speech Identification: Spoken Digit Recognition
نویسندگان
چکیده
This work presents a new Algorithm to recognize separate voices of some Arabic words, the digits form zero to ten. Firstly we prepare our signal by pre-processing trial. Next the speech signal is processed as an image by Power Spectrum Estimation. For feature extraction, transformation and hence recognition, the algorithm of minimal eigenvalues of Toeplitz matrices together with other methods of speech processing and recognition are used. At the stage of classification many methods are tested from classical ones, which depend on the matrix theory, to different types of neuron networks, mainly radial basis functions neural networks. The success rate obtained in the presented experiments is almost ideal and exceeded 98% for many cases. The results have shown flexibility to extend the algorithm to speaker identification.
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Identifying spoken language automatically is to identify a language from the speech signal. Language identification systems can be divided into two categories, spectral-based methods and phonetic-based methods. In the former, short-time characteristics of speech spectrum are extracted as a multi-dimensional vector. The statistical model of these features is then obtained for each language. The ...
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