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description Journal article public Jurnal Al-Azhar Indonesia Seri Sains dan Teknologi

Speech Recognition dengan Hidden Markov Model untuk Pengenalan dan Pelafalan Huruf Hijaiyah

Qothrun Nada, Cahya Ridhuandi, Puji Santoso, Dwi Apriyanto
Published 2019

Abstract

– The main lesson in reading the Al Qur'an is recognizing and reciting the letters Hijaiyah. Some facts show that incorrect pronunciation can affect meaning literally. Speech Recognition, as the current technology, can be used to check the mistakes in pronouncing the Hijaiyah's letter through recognizing the voice or speech. It can convert into data that can be understood by the system. The purpose of this study is to implement Speech Recognition with Hidden Markov Model for Hijaiyah letter pronunciation when learning to read the Qur'an. Speech recognition and Hidden Markov Models were carried out to develop a sound-based machine interface system. In this study also used the Fast Fourier Transform (FFT) method to extract traits. Hidden Markov Model (HMM) used in the training process. Also, produced the especially characteristics for each letter of Hijaiyah. And then, Euclidean Distance (ED) for the final classification in detecting Hijaiyah letter pronunciation. The results of the study show that the results of the Hijaiyah letter test on the same level of accuracy are 100%, while the testing of different letters is 54.6%. Thus, this study will contribute to students who are learning to read Al-Qur'an to be able to recognize and recite the Hijaiyah letters.Keywords - Speech Recognition, Hidden Markov Model, Recognizing, Reciting, Letter Hijaiyah

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