In this submission for MIREX 2014 we utilize a novel piano music transcription algorithm based on the temporal evolution of piano notes. Most existing transcription algorithms, especially those based on Non-negative matrix factorization and Probabilistic latent component analysis, operate on a spectrogram on a frame-by-frame basis, i.e., they do not consider the temporal evolution of the notes ...

We propose a new technique for modifying the time-scale of speech using Independent Subspace Analysis (ISA). To carry out ISA, the single channel mixture signal is converted to a time-frequency representation such as spectrogram. Here, the spectrogram is generated by taking Hartley or Wavelet transform on overlapped frames of speech. We do dimensionality reduction of the autocorrelated original...

We investigate the use of image processing techniques based on partial differential equations applied to the image produced by time-frequency representations of onedimensional signals, such as the spectrogram. Specifically, we use the PDE model introduced by Álvarez, Lions and Morel for noise smoothing and edge enhancement, which we show to be stable under signal and window perturbations in the...

A filterbank-based algorithm for time-varying spectral analysis is proposed. The algorithm, which is an enhanced realization of the conventional spectrogram, consists of hundreds or thousands of highly overlapping wideband filter/detector stages, followed by a peak detector that probes the filter/detector outputs at very short time intervals. Analysis with synthetic modulated signals illustrate...

Feature extraction is a crucial part of many MIR tasks. Many manual-selected features such as MFCC have been applied to music processing but they are not effective for music genre classification. In this work, we present an algorithm based on spectrogram and convolutional neural network (CNN). Compared with MFCC, the spectrogram contains more details of music components such as pitch, flux, etc...

The intelligence term can be view in many areas such as linguistic, mathematical, music and art. In this paper, the Intelligence Quotient (IQ) is measured using Electroencephalogram (EEG) from the human brain. The spectrogram images were formed from EEG signals, then the Gray Level Co-occurrence Matrix (GLCM) texture feature were extracted from the images. This texture feature produced big matr...

We extend the spectrum estimation method of Thomson to non-stationary signals by formulating a multiple window spectrogram. The traditional spectrogram can be represented as a member of Cohen’s class of time-frequency distributions (TFDs), where the smoothing kernel is the Wigner distribution of the signal temporal window. We show the unusual shape of the Cohen’s class smoothing kernels corresp...