DETEKSI SUARA UCAPAN SALAM BAHASA ARAB MENGGUNAKAN MEL FREQUENCY CEPSTRAL COEFFICIENT (MFCC) DAN PEMILIHAN FITUR MIN MAX
Abstract
Abstract
Arabic greeting sounds are used in everyday life for Muslims in Indonesia. Salam recognition is used to check how correct the pronunciation of Arabic greetings is for Indonesians. The first stage was to collect the sample of greeting readings as much as 50 records of male and female records in wav recordings. One person takes the source of greeting reading as a reference for reference. Retrieval of test data as much as 50 samples of test data. The second stage is to perform feature extraction with MFCC from cepstral coefficient and frame results. The third stage is testing by checking the suitability of the greeting reading with the calculation of min max. The result of checking the suitability of reading on the selection of the right features carried out by MFCC has a result of 60.25%. Meanwhile, MFCC with a minimum yield of 71.75.0%. This shows that the use of the min max test can improve accuracy because there are more unique cepstral and max and min coefficients with a significant difference of 11.5%.
Keywords : checking, feature extraction, reference, features, speech
Suara ucapan salam bahasa Arab digunakan dalam kehidupan sehari-hari bagi umat beragama Islam di Indonesia. Pengenal ucapan salam dilakukan untuk mengecek seberapa benar dalam pelafalan ucapan salam berbahasa Arab bagi orang Indonesia. Tahap pertama dilakukan pengambilan sampel bacaan salam sebanyak 50 data rakaman putra dan putri dalam rekaman wav. Pengambilan sumber bacaan salam diambil satu orang sebagai acuan untuk referensi. Pengambilan data uji sebanyak 50 sampel data uji. Tahap kedua adalah melakukan ekstraksi ciri dengan MFCC hasil cepstral coeficient dan frame. Tahap ketiga adalah pengujian dengan pengecekan kesesuaian bacaan salam dengan perhitungan min max. Hasil pengujian pengecekan kesesuaian bacaan terhadap pemilihan fitur yang tepat dilakukan dengan MFCC mempunyai hasil sebesar 60,25%. Sedangkan MFCC dengan min max hasil sebesar 71.75,0%. Hal tersebut menunjukkan bahwa penggunaan pengujian min max dapat meningkatkan akurasi karena terdapat cepstral dan coefficients max dan min lebih unik dengan selisih 11.5% cukup signifikan
Kata Kunci : pengecekan, ekstraksi ciri, referensi, fitur, ucapan
Keywords
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