Abstract

Bugis language is one of the traditional languages in South Sulawesi which has various dialects. Different ways of speaking and tone of voice that cause voice of each person also vary. The design of the Bugis language speech recognition system is one way to digitize and indicate the Bugis regional language. This study uses Mel Frequency Cepstral Coefficient (MFCC) method as a feature extraction and Adaptive Neuro-Fuzzy Inference System (ANFIS) as an algorithm for classification and recognition. This research was conducted by collecting various voice data from various age groups and regions. Voice data is collected in wav audio format and then extracted into numerical results to use as database on system. Test was carried out using various database models and the amount of voice data. The test results show that databases with single data produce a higher level of accuracy with a percentage of truth above 50%. While the test results with a database of 37 speakers with a total data of 740 have a low level of accuracy and are below 50%. Testing in outdoors has a lower accuracy around 10%. Error value in the data training process in the range of 0.5 - 1.5.

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