Change detection within an audio stream is an important task in several domains, such as classification and segmentation of a sound or of a music piece, as well as indexing of broadcast news or surveillance applications. In this paper we propose two novel methods for spectral change detection without any assumption about the input sound: they are both based on the evaluation of information meas...

The frequency contents of the non-stationary signals vary with time. For proper characterization of such signals, a smart time-frequency representation is necessary. Classically, the STFT (short-time Fourier transform) is employed for this purpose. Its limitation is the fixed timefrequency resolution. To overcome this drawback an enhanced STFT version is devised. It is based on the signal drive...

An auditory-perception inspired singing voice separation algorithm for monaural music recordings is proposed in this paper. Under the framework of computational auditory scene analysis (CASA), the music recordings are first transformed into auditory spectrograms. After extracting the spectral-temporal modulation contents of the timefrequency (T-F) units through a two-stage auditory model, we de...

The paper presents an adaptive time-frequency denoising algorithm. Other denoising methods use a very general probability-based noise model and as general-purpose algorithms rarely consider the a priori knowledge about the signal. Main novelty of the proposed algorithm is the running quasi-continuous scalo-temporal model of background activity built and subtracted from the ECG in order to yield...

Gabor deconvolution has been updated and a new ProMAX module is released. The updates are: (1) a new method of spectral smoothing called hyperbolic smoothing; (2) a Gabor transform using compactly supported windows that improves run times by one to two orders of magnitude; and (3) a post-deconvolution time-variant bandpass filter whose maximum frequency tracks along a hyperbola in the time-freq...

In this paper, a method for automatic transcription of music signals using a convolutive probabilistic model is proposed, by extending the shift-invariant Probabilistic Latent Component Analysis method. Several note templates from multiple orchestral instruments are extracted from monophonic recordings and are used for training the transcription system. By incorporating shift-invariance into th...

A set of binaural time-recordings and analyses of wind turbine noise outside and inside a residence in Huron County, Michigan, made over two days and the intervening night in December 2009, is presented, centering on analysis at the time/frequency resolutions of human hearing according to the well-established practices of sound quality engineering and Soundscaping [1]. The purpose of this paper...

The EEG signals are recorded between electrodes placed in standard positions on the scalp. They have a typical amplitude of 2-100 μV and a frequency spectrum from 0.1 ÷ 50 Hz. The potential at the scalp derives from electrical activity of large synchronized groups of neurons inside the brain. EEG activity in particular frequency bands is often correlated with particular cognitive states. There ...

Our proposed hyper kurtosis based histogram equalized DIC images enhances the contrast by preserving the brightness. The evolution and development of precancerous activity among tissues are studied through S-transform (ST). The significant variations of amplitude spectra can be observed due to increased medium roughness from normal tissue were observed in time-frequency domain. The randomness a...

Natural signals are often characterized by a complex timefrequency behaviour. These signals exist in many different applications and systems from underwater acoustic to audio signals with sound attacks or electrical systems with partial discharges and commutation switches, for example. There is a huge number of Time-Frequency (TF) methods that aim to characterize these signals in terms of first...