Voice detection is very important for the world of information technology that can be used for voice processing, biometrics, human computer interfaces. Voice identification carried out in this study is based on speech or dialect using a prototype that has been designed using the Raspiberry Pi device and other supporting devices. In its application, the regional identification prototype uses sound feature extraction, namely Mel Frequency Cepstral Coefficients (MFCC) and uses an artificial neural network method with a multilayer perceptron (secos) developing algorithm. The purpose of this study is to identify regional origins based on dialect or speech using the Mel Frequency Cepstral Coefficients (MFCC) extraction technique and the Evolving Multilayer Perceptron method. The results of the regional recognition test produce a good level of accuracy, with testing as an example of the Aceh area with test data of 10 voice samples, the results obtained by the prototype can identify voices with a success rat of being able to recognize 7 voices out of 10 samples tested in the Aceh region. From all the tests on the areas of Aceh, Karo, Nias, Simalungun, the accuracy was 88%