ABSTRAK – Teknologi biometrik sedang menjadi tren teknologi dalam berbagai bidang kehidupan. memanfaatkan bagian tubuh manusia sebagai alat ukur sistem yang memiliki keunikan disetiap individu. Suara merupakan dan cocok dijadikan mengadopsi biometrik. Sistem pengenalan suara adalah salah satu penerapan fokus kepada manusia. memerlukan metode ekstraksi fitur klasifikasi, MFCC. MFCC dimulai dari ...

An approach to speech feature detection is developed, which uses the technique of independent component analysis for a blind (unsupervised learning) detection of basic vectors in the Fourier space. This kind of features could replace the Mel Frequency Cepstrum Coefficient (MFCC) features, widely used today for phoneme-based speech recognition. Alternatively, the ICA components could act as basi...

This paper describes the development of an efficient speech recognition system using various techniques such as Mel Frequency Cepstrum Coefficients (MFCC), Vector Quantization (VQ), Hidden Markov Model (HMM) and Autocorrelation. In this paper, a method to recognize the speech faster with more accuracy, speaker recognition is followed by speech recognition. MFCC/Autocorrelation is used to extrac...

In this paper, a drive-by damage detection methodology for high-speed railway (HSR) bridges is addressed, to appraise the application of Mel-frequency cepstral coefficients (MFCC) extract Damage Index (DI). A finite element (FEM) 2D VTBI model that incorporates train, ballasted track and bridge behavior presented. The formulation includes irregularities damaged condition induced in specified st...

The Cerebellar Model Articulation Controller (CMAC) and fuzzy systems have been active areas of research since its initial introduction. Fuzzy CMAC is basically a CMAC that is coupled with a fuzzy system. This paper presents the incorporation of fuzzy systems into CMAC with Approximate Analogical Reasoning Scheme (AARS) as its inference rules and Discrete Incremental Clustering (DIC) as its tec...

The author investigates automatic recognition of singers’ gender and age through audio features using deep neural network (DNN). Features of each singing voice, fundamental frequency and Mel-Frequency Cepstrum Coefficients (MFCC) are extracted for neural network training. 10,000 singing voice from Smule’s Sing! Karaoke app is used for training and evaluation, and the DNN-based method achieves a...

The main bearing is the core component of gas-fired generator, and its reliability directly affects stability whole system. Therefore, it great significance to study fault diagnosis generator. In based on vibration signal, how extract signature features effectively key achieving accurate diagnosis. Based extracting faults, classify efficiently another this, we propose a method Mel frequency cep...

We apply the technique of independent component analysis to Fourier power coefficients of speech signal frames for a blind detection of basic vectors (sources). A subset of sources corresponding to the noisy influence of basic frequency is identified and its corresponding features could be eliminated. The mixing coefficients for such sources are then determined for every speech sample. We compa...

The paper present effective method for recognition of digit, numbers. Most of speech recognition systems contain two main modules as follow “feature extraction” and “feature matching”. In this project, (MFCC) Mel Frequency Cepstrum coefficient algorithm is used to simulate feature extraction module. Using this algorithm, the Cepstral Coefficients are calculated on Mel frequency scale. VQ (vecto...