where w(n) is an analysis window. At each time instant, the STFT is a discrete-time Fourier transform or discrete Fourier transform (DFT). Many DFT computing algorithms and architectures have been proposed. However, the direct use of the DFI' without considering the special sliding window effect of STFT is not an efficient approach. There are two major approaches for STFT. One is based on the f...

Musical onset detection is a key component in any beat tracking system. Existing algorithms for onset detection usually rely on short time Fourier transform (STFT). Of numerous existing methods to detect musical onsets, a common limitation is the genre-specific performance. For example, accurate onset locations are not usually identified for genres such as classical music and opera music. In th...

This paper describes techniques for obtaining high accuracy estimates, including those of non-stationarity, of parameters for sinusoidal modelling using a single frame of analysis data. In this case the data used is generated from the time and frequency reassigned short-time Fourier transform (STFT). Such a system offers the potential for quasi real-time (frame-by-frame) spectral modelling of a...

In this paper, a new adaptive Fourier decomposition (AFD) based time-frequency speech analysis approach is proposed. Given the fact that the fundamental frequency of speech signals often undergo fluctuation, the classical short-time Fourier transform (STFT) based spectrogram analysis suffers from the difficulty of window size selection. AFD is a newly developed signal decomposition theory. It i...

EEG signals recorded from scalp contain useful information about the activity of a large number of neurons. Signal processing is needed to extract this information from the EEG signal. Here we study the effects of configurations of Short Time Fourier Transform (STFT) to determine how the parameters of STFT affect spectral estimations of the mean and relative power in beta and gamma frequency ba...

The Fourier transform is an integral part of signal processing of any kind. To be able to analyze an input signal as a superposition of infinitely many signals of different frequency allows for manipulation of the coefficients and, after completing the inverse Fourier transform, interesting effects on the initial signal. Thus, in my project I focused on creating pitch correction effects as seen...

Typical speech enhancement algorithms that operate in the Fourier domain only modify the magnitude component. It is commonly understood that the phase component is perceptually unimportant, and thus, it is passed directly to the output. In recent intelligibility experiments, it has been reported that the Short-Time Fourier Transform (STFT) phase spectrum can provide significant intelligibility ...

This paper investigate the circularity of Short Time Fourier Transform (STFT) coefficients noise only, and proposes a modified STFT such that all coefficients coming from white Gaussian noise are circular. In order to make use of the spectral kurtosis (SK) for a stop criterion, we consider the spectral kurtosis of circular random variables, and its link with the kurtosis of the real and imagina...

This paper is part 6 in a series of papers about the Discrete Fourier Transform (DFT) and the Inverse Discrete Fourier Transform (IDFT). The focus of this paper is on correlation. The correlation is performed in the time domain (slow correlation) and in the frequency domain using a Short-Time Fourier Transform (STFT). When the Fourier transform is an FFT, the correlation is said to be a " fast ...

This paper is part 4 in a series of papers about the Discrete Fourier Transform (DFT) and the Inverse Discrete Fourier Transform (IDFT). The focus of this paper is on spectral leakage. Spectral leakage applies to all forms of DFT, including the FFT (Fast Fourier Transform) and the IFFT (Inverse Fast Fourier Transform). We demonstrate an approach to mitigating spectral leakage based on windowing...