Aplikasi Pengenalan Ucapan dengan Ekstraksi Mel-Frequency Cepstrum Coefficients (MFCC) Melalui Jaringan Syaraf Tiruan (JST) Learning Vector Quantization (LVQ) untuk Mengoperasikan Kursor Komputer
ABSTRACT: During this time,
computer cursor operation was done by pressing and moving the mouse. So, this
is less flexible for computer user that require movement in operating a
computer, since to use mouse comfortably someone has to sit. Moreover, physical
completeness is required for mouse operating, so that for someone who has
physical disabilities feels difficult to operate it. Therefore, it is required
to develop a system that provides a better comfort and flexibility not only for
the healthy user computer but also for the user computer who has physical
disabilities. In this final project, computer cursor operation program via
voice is created. With this program, someone will have more flexibility when
operating the computer cursor and also people with physical disabilities is
enabled to communicate with computer. Voice recognition is a technology that is
apllied in this program, with the feature extraction process used MFCC
(Mel-Frequency Cepstrum Coefficients) method. As for the recognitions process
used artificial neural network type LVQ (Learning Vector Quantization). Voice
is passed through a microphone and then it is analyzed by MFCC to produce MFCC
coefficients. These coefficients are used as input vector for LVQ neural
network and used as data to train the network until it has the classification
capability. Programming language that is used in creating this software is
Delphi programming language. Based on the result of the testing program, it is
found that the success percentage rate of voice recognition with training data,
that is data which is derived from databases that have been recorded and
trained into the program which amounts to 240 data, is 88,89 %. While in the
testing with test data, that is data which is derived from the real time
sayings of respondents which is amounts to 240 data, it is found that the
success percentage rate of voice recognition is 83,99 %.
Penulis: ANGGA SETIAWAN,
ACHMAD HIDAYATNO, R. RIZAL ISNANTO
Kode Jurnal: jptlisetrodd110129
