SISTEM PENGENALAN UCAPAN HURUF VOKAL MENGGUNAKAN METODE LINEAR PREDICTIVE CODING (LPC) DAN JARINGAN SARAF TIRUAN LEARNING VECTOR QUANTIZATION (LVQ) BERBASIS MIKROKONTROLER

LESTARI, DESI (2014) SISTEM PENGENALAN UCAPAN HURUF VOKAL MENGGUNAKAN METODE LINEAR PREDICTIVE CODING (LPC) DAN JARINGAN SARAF TIRUAN LEARNING VECTOR QUANTIZATION (LVQ) BERBASIS MIKROKONTROLER. Fakultas Teknologi Informasi.

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Abstract

ABSTRACT VOWEL SPEECH RECOGNITION SYSTEM USING LINEAR PREDICTIVE CODING (LPC) METHOD AND NEURAL NETWORK LEARNING VECTOR QUANTIZATION (LVQ) BASED MICROCONTROLLER By Desi Lestari 0910452031 Speech recognition system is the development of techniques and systems that enable the technology to be able to accept spoken voice input, recognize and translate. Now, speech recognition system into something that is very functional in the field of communication technology, because speech can be a medium to interact with the existing technology. Therefore it takes a device or system that is able to recognize and translate the sounds of human speech. In this final task of making speech recognition system to the sound / a / / i / / u / / e / and / o / by using the voice feature extraction algorithm, namely LPC. LPC is one method of voice signal analysis stating the essential features of the voice signal in the form of LPC coefficients. By making the process preemphasis, windowing, autocorrelation and LPC analysis, then the obtained difference characteristics of the speech signal coefficient values. As for the classification and identification of speech used by the Neural Network algorithm LVQ. LVQ training process will produce a final weight values for each vowel utterance. So the value of the final weight will be the weight of a reference for phase identification vowel speech recognition. From the results of the testing that has been done to the vowel speech recognition system is known that the introduction of a new speech utterance to lower the data to the data of training speech. With a success rate of data speech recognition training is 80% and for the introduction of the new pronunciation of data by 40%. Keywords: Speech recognition, LPC, artificial neural networks, LVQ

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