Spectrogram factorization methods have been proposed for single channel source separation [1–4], audio analysis [5–8] and more recently multichannel source separation [9–11]. All spectrogram factorization approaches incorrectly assume that the mixture spectrogram is the sum of the source spectrograms. In fact, the mixture spectrogram depends on the source spectrograms and the phase difference b...

We propose a multi-channel speech dereverberation approach based on cross-channel cancellation and spectrogram decomposition. The reverberation is modeled as a convolution operation in the spectrogram magnitude domain. Using the Itakura divergence (I-divergence), we decompose reverberant spectrogram into clean spectrogram convolved with a deconvolution filter. The speech spectrogram is constrai...

Sound-event classification often extracts features from an image-like spectrogram. Recent approaches such as spectrogram image feature and subband-power-distribution image feature extract local statistics such as mean and variance from the spectrogram. We argue that such simple image statistics cannot well capture complex texture details of the spectrogram. Thus, we propose to extract pseudo-co...

As many acoustic signal processing methods, for example for source separation or noise canceling, operate in the magnitude spectrogram domain, the problem of reconstructing a perceptually good sounding signal from a modified magnitude spectrogram, and more generally to understand what makes a spectrogram consistent, is very important. In this article, we derive the constraints which a set of co...

objective: to obtain abnormalities in quantitative electroencephalography qeeg) and to observe connectivity between electrodes in children with asperger disorder. method: in this study, spectrogram criteria and coherence values are used as a tool for evaluating qeeg in 15 children with asperger disorder (10 boys and 5 girls aged between 6 to 11 years old) and in 11 control children boys and 4 g...

A novel technique of unmasking to repair the degradation in sources separated by spectrogram masking is proposed. Our approach is based on explicit knowledge of the musical audio at note level from a score-audio alignment, which we termed Informed Source Separation (ISS). Such knowledge allows the spectrogram energy to be decomposed into note-based models. We assume that a spectrogram mask for ...

Since the invention of the sound spectrograph in 1946 by Koenig, Dunn and Lacey, spectrograms have been widely used for speech research. Over the last decade there has been revived interest in the application of spectrogram reading toward continuous speech recognition. Spectrogram reading involves interpreting the acoustic patterns in the image to determine the spoken utterance. One must select...

This paper presents novel approaches for efficient feature extraction using environmental sound magnitude spectrogram. We propose approach based on the visual domain. This approach included three methods. The first method is based on extraction for each spectrogram a single log-Gabor filter followed by mutual information procedure. In the second method, the spectrogram is passed by the same ste...