In this paper, we present a content-based classification approach for audio indexing. The classification is based on low level audio features such as temporal sound, energy, fundamental frequency, zero crossing rate, auto correlation curve, and based on transformations such as Short Time Fourier Transform (STFT). The audio classification in classes such as music, noise, silence, and speech is a...

Adaptive whitening is a preprocessing technique for STFTbased onset detectors, which can improve the performance of onset detectors by compensating for spectral rolloff and dynamic variability [7]. In this MIREX submission we applied adaptive whitening to a selection of STFT-based onset detection functions (ODFs) from recent literature. Our code is oriented primarily towards use in real-time sy...

Abstract Electroencephalography (EEG) allows recording of cortical activity at high temporal resolution. Creating features useful for the analysis EEG can be challenging. Here we introduce a new method pre-processing time-series resting state and binary task classification using recurrence quantification (RQA) compare it with existing state-of-the-art approach based on signal embedding. To reve...

The Short-Time Fourier transform (STFT) is a helpful tool to identify muscle fatigue with clinical and sports applications. However, the choice of STFT parameters may affect estimation myoelectrical manifestations fatigue. Here, we determine effect window length overlap selections on frequency slope coefficient variation from EMG spectrum features in fatiguing contractions. We also whether rela...

Analysis of non stationary signals like audio, speech and biomedical signals require good resolution both in time and frequency as their spectral components are not fixed. There are many applications of time-frequency analysis in non stationary signals like source separation, signal denoising etc. This paper presents an application of time frequency analysis using STFT, Short Time Fourier Trans...

For audio source separation applications, it is common to estimate the magnitude of the Time-Frequency (TF) representation of each source. In order to recover a time-domain signal from a spectrogram for instance, it then becomes necessary to recover the phase of the corresponding complex-valued ShortTime Fourier Transform (STFT). Most authors in this field choose a Wiener-like filtering approac...

This paper takes the opportunity of presenting a set of new adaptive effects to propose a generic scheme for adaptive effects built upon a spectral source-filter decomposition and a Short-Time Fourier analysis-resynthesis. This allows for a better formalization of the involved signal processing algorithms and leads to a simple classification of adaptive effects already presented in the literatu...