Speech is the effective form of communication between human and its environment. Dysarthria is a motor speech disorder in which the person lacks the control over articulators used for speech production. Speech accuracy is the outcome of well-timed and coordinated activities of the articulators and other related neuro muscular feature. In this paper, Speech utterance is converted into a phone se...

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...

This paper presents a quantitative metric to describe the multidimensionality of spectral envelope perception, that is, the perception specifically related to the spectral element of timbre. Mel-cepstrum (Mel-frequency cepstral coefficients or MFCCs) is chosen as a hypothetical metric for spectral envelope perception due to its desirable properties of linearity, orthogonality, and multidimensio...

This paper presents the work on Automatic Speech Recognition of Urdu language, using a comparative analysis for Discrete Wavelets Transform (DWT) based features and Mel Frequency Cepstral Coefficients (MFCC). These features have been extracted for one hundred isolated words of Urdu, each word uttered by ten different speakers. The words have been selected from the most frequently used words of ...

This paper describes a medium size Bangla speech corpus preparation and the comparison of the performances of different acoustic features for Bangla word recognition. A small number of speakers are use for most of the Bangla automatic speech recognition (ASR) system, but 40 speakers selected from a wide area of Bangladesh, where Bangla is used as a native language, are involved here. In the exp...

Automatic speech recognition by machine is one of the most efficient methods for man-machine communications. Because speech waveform is nonlinear and variant. Speech recognition requires a lot of intelligence and fault tolerance in the pattern recognition algorithms. Accurate vowel recognition forms the backbone of most successful speech recognition systems. A collection of techniques exists to...

Three different methodologies for automatic speaker identification have been evaluated in the paper, namely the well known Dynamic Time Warping (DTW), the Auto-Regressive Vector Models (ARVM) and an Algebraic Approach (AA). The aim of our study is to examine the effectiveness of these approaches in the fixed-text speaker identification task with short phrases in Bulgarian language collected ove...

An algorithm involving Mel-Frequency Cepstral Coefficients (MFCCs) is provided to perform signal feature extraction for the task of speaker accent recognition. Then different classifiers are compared based on the MFCC feature. For each signal, the mean vector of MFCC matrix is used as an input vector for pattern recognition. A sample of 330 signals, containing 165 US voice and 165 non-US voice,...

Data Science is a fairly novel field, and it predominantly deals with analysis assortment of data. Machine Learning field that goes hand in this regard. Various Algorithms, which are trained on dataset predict results based their training, thus the accuracy model determined by testing dataset. Foreground feature extraction another interesting application. Using data visualization processing, we...

In this paper, novel Variable length Teager Energy Operator (VTEO) based Mel cepstral features, viz., VTMFCC are proposed for automatic classification of normal and pathological voices. Experiments have been carried out using this proposed feature set, MFCC and their score-level fusion. Classification was performed using a 2 order polynomial classifier on a subset of the MEEI database. The equa...