Language identification is at the forefront of assistance in many applications, including multilingual speech systems, spoken language translation, recognition, and human-machine interaction via voice. The indonesian local languages using technology has enormous potential to advance tourism digital content Indonesia. goal this study identify four Indonesian languages: Javanese, Sundanese, Minan...

The detection of leaks in water distribution systems (WDS) has always been a major concern for urban supply companies. However, the performance traditional leak classifiers highly depends on effectiveness handcrafted features. An alternative method is to use convolutional neural network (CNN) process raw signals directly obtain deep representations that may ignore prior information about leakag...

obtaining a seismic section with high temporal and spatial resolution was always one of the goals of seismic data processors and interpreters. accurate estimation of the thicknesses of thin beds is an important tool in this regard. the basic problem is that the wavelength of the signal must be similar in dimention to that of the bed thinness. if it is much longer than the bed thinness, the dete...

The goal of speech parameterization is to extract the relevant information about what is being spoken from the audio signal. In speech recognition systems Mel-Frequency Cepstral Coefficients (MFCC) and Relative Spectral Mel-Frequency Cepstral Coefficients (RASTA-MFCC) are the two main techniques used. It will be shown in this paper that it presents some modifications to the original MFCC method...

In this paper, we investigate the noise-robustness of features based on the cepstral time coefficients (CTC). By cepstral time coefficients, we mean the coefficients obtained from applying the discrete cosine transform to the commonly used mel-frequency cepstral coefficients (MFCC). Furthermore, we apply temporal filters used for computing delta and acceleration dynamic features to the CTC, res...

In this paper, we propose several compensation approaches to alleviate the effect of additive noise on speech features for speech recognition. These approaches are simple yet efficient noise reduction techniques that use online constructed pseudo stereo codebooks to evaluate the statistics in both clean and noisy environments. The process yields transforms for noisecorrupted speech features to ...

This paper proposes fusion and addition techniques of vocal tract features such as Mel Frequency Cepstral Coefficients (MFCC) and Dynamic Mel Frequency Cepstral Coefficients (DMFCC) in speaker identification. Feature extraction plays an important role as a front end processing block in Speaker Identification (SI) process. Mel frequency features are used to extract the spectral characteristics o...

This paper addresses the performance of various statistical data fusion techniques for combining the complementary score information in speaker verification. The complementary verification scores are based on the static and delta cepstral features. Both LPCC (Linear prediction-based cepstral coefficients) and MFCC (mel-frequency cepstral coefficients) are considered in the study. The experiment...

This project's 'HMM Based Automatic Speech Recognition Analysis main motive is just to generate an Automatic speech recognition which is clear an accurate using Hidden Markov Model (HMM) to get accurate results at number of frequency ranges related to human voice. Here is a record of 12 different words which is recorded by using a number of different speakers that includes male and female both ...