The analysis and classification of audio signals are becoming increasingly important, especially in the age communication dissemination information through radio broadcasting systems. It is therefore essential that systems platforms available to monitor spread fake or fraudulent news. A speech feature-based correlation (SFC) algorithm a recognition framework developed this study, combining spec...

Dyadic scheme of wavelet signal decomposition leads to a specific division of frequency bands. It is comparable to mel-frequency division and may be used in effective parameterization of speech signal in recognition systems, speech coding or other speech signal based applications. This paper discusses efficiency of different spectral distance measures applied to wavelet-parameterized speech. Th...

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 noise-corrupted speech features to...

This paper presents the robust front-end algorithm that was submitted by Motorola to the ETSI STQ-Aurora DSR working group as a proposal for the Advanced DSR front-end in January 2001. The algorithm consists of a two-stage melwarped Wiener filter, a waveform processor, a channelnormalized mel-frequency cepstral calculation and a subsystem of post-cepstral processing according to the reliability...

Acoustic analysis is a proper method in vocal fold pathology diagnosis so that it can complement and in some cases replace the other invasive, based on direct vocal fold observation, methods. There are different approaches for vocal fold pathology diagnosis. These algorithms usually have two stages which are Feature Extraction and Classification. While the second stage implies a choice of a var...

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...

Detecting distinct features in modern pop music is an important problem that can have significant applications in areas such as multimedia entertainment. They can be used, for example, to give a visually coherent representation of the sound. We propose to integrate a singing voice detector with a multimedia, multi-touch game where the user has to perform simple tasks at certain key points in th...

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 ...

Artiicial neural networks (ANNs) have been used to classify phonetic features in speech. The feature streams from the ANNs are used here as the observations for Hidden Markov Models (HMMs). Using such observations allows us to build a competitive speech recogniser. This recogniser is compared to a similar recogniser that was trained on mel-frequency cepstral coeecients (MFCCs). While the cepstr...

The objective of the presentation is to report experiments involving the automatic classification of disordered connected speech into binary (normal, pathological) or multiple (modal, moderately hoarse, severely hoarse) categories. The multicategory classification according to the perceived degree of hoarseness is considered to be clinically meaningful and desirable given that the reliable perc...