Sound Matching on The Translation of Al-Quran Ayates as Childrens Learning Media Using Fast Fourier Transform (FFT) Algorithm and Mobile Conquer Divide
Moch Abdurrodjak, Maulana Hasan, Izzah Faizah SR. Khaerani, Husnul Qodim, Busro Busro
1,2,3,4 UIN Sunan Gunung Djati Bandung
5 STMIK Primakara
Abstract
Speech recognition is a process of recognizing letters, words or sentences that are spoken. Voice recognition is better known as Automatic Speech Recognition (ASR). Automatic Speech Recognition (ASR) has been widely applied in everyday life, for example is the operation of a smartphone that is run through automatic commands (voice recognition). The letter of origin is the place where the letter is released when the letter is pronounced. The letter of origin is the basis for reading the verses of the Koran. Errors in the pronunciation of letters or in makhraj letters, can cause differences in meaning or meaning errors in the verse being read. Generally the method of learning to read the Koran is used accompanied by accompanying teachers who are proficient in their fields. In this final project, a sound matching application was built on the pronunciation of Ayat Al-Quran as a learning medium for children using the Fast Fourier Transform (FFT) Algorithm and Divide Conquer (DC) that support learning independently. The system built in the final project is to utilize the Google API feature on android as voice matching. Furthermore, the incoming sound will convert into text form using the Google API. The conversion method used is Fast Fourier Transform (FFT). The valuation method, Divide Conquer is used by calculating the sound proximity value of the Google API conversion results by matching Arabic text in the database. Based on the testing that has been done on the system testing. The results of the test found 61.1% accuracy for the appropriate reading and 38.9% for inappropriate reading.
Keywords: Sound Matching, Google API, Divide Conquer
Topic: Computer and Communication Engineering