ORTHONORMAL-BASIS PARTITIONING AND TIME-FREQUENCY REPRESENTATION OF NON-STATIONARY SIGNALS Benhur Aysin, Ph.D. University of Pittsburgh, 2002 Spectral analysis is important in many fields, such as speech, radar and biomedicine. Many signals encountered in these areas possess time-varying spectral characteristics. The power spectrum indicates what frequencies exist in the signal but it does not ...

Recently, we have witnessed an increasing use of the sourcefilter model in music analysis, which is achieved by integrating the source filter model into a non-negative matrix factorisation (NMF) framework or statistical models. The combination of the source-filter model and NMF framework reduces the number of free parameters needed and makes the model more flexible to extend. This paper compare...

This paper introduces a new score-informed method for the segmentation of jingju a cappella singing phrase into syllables. The proposed method estimates the most likely sequence of syllable boundaries given the estimated syllable onset detection function (ODF) and its score. Throughout the paper, we first examine the jingju syllables structure and propose a definition of the term “syllable onse...

We present an algorithm for removing timefrequency components, found by a standard Gabor transform, of a “real-world” sound while causing no audible difference to the original sound after resynthesis. Thus this representation is made sparser. The selection of removable components is based on a simple model of simultaneous masking in the auditory system. Important goals were the applicability to...

7 (+ $< " Markus Till and Stephan Rudolph Institute for Statics and Dynamics of Aerospace Structures University Stuttgart, Pfaffenwaldring 27, D-70569 Stuttgart, Germany Proceedings SPIE Conference On Applications and Science of Computation al Intelligence III, Orlando, Florida, April 24-28th, 2000 ABSTRACT Successful signal classification requires the selection of a problem-oriented signal rep...

In this paper, we present a novel methodology for sports highlight detection based on audio information. For processing the sounds of sports events, we propose a timefrequency feature extraction method computing local autocorrelations on complex Fourier values (FLAC). For highlights detection, we apply (complex) subspace method to the extracted FLAC features to detect the “exciting” scenes whic...

In order to improve the time-frequency resolutions of short-time fractional Fourier transform, adaptive short-time fractional Fourier transform (ASTFRFT) method is used in this paper. The optimal order of ASTFRFT is given by maximizing kurtosis of signals in fractional domain, where the window width of ASTFRFT is searched by the maximal Shannon entropy of timefrequency distribution. Short-time ...

We present a review of the diversity of concepts and motivations for improving the concentration and resolution of timefrequency distributions (TFDs) along the individual components of the multi-component signals. The central idea has been to obtain a distribution that represents the signal’s energy concentration simultaneously in time and frequency without blur and crosscomponents so that clos...