Jesper Højvang Jensen

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We present a distance measure between audio files designed to identify cover songs, which are new renditions of previously recorded songs. For each song we compute the chromagram, remove phase information and apply exponentially distributed bands in order to obtain a feature matrix that compactly describes a song and is insensitive to changes in(More)
We introduce a representation for rhythmic patterns that is insensitive to minor tempo deviations and that has well-defined behavior for larger changes in tempo. We have combined the representation with an Euclidean distance measure and compared it to other systems in a classification task of ballroom music. Compared to the other systems, the proposed(More)
In music similarity and in the related task of genre classification , a distance measure between Gaussian mixture models is frequently needed. We present a comparison of the Kullback-Leibler distance, the earth movers distance and the normalized L2 distance for this application. Although the normalized L2 distance was slightly inferior to the(More)
Recently, two optimal filter designs for fundamental frequency estimation have been proposed with the first being based on a filterbank and the second on a single filter. The two designs are related in a simple manner and are shown to result in the same residual when used for cancelling out the harmonics of periodic signals. We propose to use this residual(More)
For music information retrieval tasks, a nearest neighbor classifier using the Kullback-Leibler divergence between Gaussian mixture models of songs' melfrequency cepstral coefficients is commonly used to match songs by timbre. In this paper, we analyze this distance measure analytically and experimentally by the use of synthesized MIDI files, and we find(More)
Spectral envelope parameters in the form of mel-frequency cepstral coefficients are often used for capturing timbral information of music signals in connection with genre classification applications. In this paper, we evaluate mel-frequency cepstral coefficient (MFCC) estimation techniques, namely the classical FFT and linear prediction based(More)
Recently, we proposed using Capon's minimum variance principle to find the fundamental frequency of a periodic waveform. The resulting estimator is formed such that it maximizes the output power of a bank of filters. We present an alternative optimal single filter design and then proceed to quantify the similarities and differences between the estimators(More)
To analyze specific properties of music similarity measures that the commonly used genre classification evaluation procedure does not reveal, we introduce a MIDI based test framework for music similarity measures. We introduce the framework by example and thus outline an experiment to analyze the dependency of a music similarity measure on the(More)
We show that by considering the estimation of the amplitudes of sinusoids in colored, Gaussian noise as a joint amplitude and noise covariance matrix estimation problem, we obtain an iterative estimator that has the Capon spectral estimator as a special case. The estimator is also closely related to the amplitude and phase estimator (APES). In experiments,(More)