Tue Lehn-Schiøler

Learn More
The process of representing a large data set with a smaller number of vectors in the best possible way, also known as vector quantization, has been intensively studied in the recent years. Very efficient algorithms like the Kohonen self-organizing map (SOM) and the Linde Buzo Gray (LBG) algorithm have been devised. In this paper a physical approach to the(More)
In large MP3 databases, files are typically generated with different parameter settings, i.e., bit rate and sampling rates. This is of concern for MIR applications, as encoding difference can potentially confound meta-data estimation and similarity evaluation. In this paper we will discuss the influence of MP3 coding for the Mel frequency cepstral(More)
Using a Parzen density estimator, any distribution can be approximated arbitrarily close by a sum of kernels. In particle filtering, this fact is utilized to estimate a probability density function with Dirac delta kernels; when the distribution is discretized it becomes possible to solve an otherwise intractable integral. In this work, we propose to extend(More)
In this paper we propose to use an instantaneous ICA method (BLUES) to separate the instruments in a real music stereo recording. We combine two strong separation techniques to segregate instruments from a mixture: ICA and binary time-frequency masking. By combining the methods, we are able to make use of the fact that the sources are differently(More)
In this paper a system that transforms speech waveforms to animated faces are proposed. The system relies on continuous state space models to perform the mapping, this makes it possible to ensure video with no sudden jumps and allows continuous control of the parameters in ’face space’. The performance of the system is critically dependent on the number of(More)
In the Bayesian modeling framework there is a close relation between regularization and the prior distribution over parameters. For prior distributions in the exponential family, we show that the optimal hyper-parameter, i.e., the optimal strength of regularization, satisfies a simple relation: The expectation of the regularization function, i.e., takes the(More)
This demonstration illustrates how the methods developed in the MIR community can be used to provide real-time feedback to music users. By creating a genre classifier plugin for a popular media player we present users with relevant information as they play their songs. The plug-in can furthermore be used as a data collection platform. After informed consent(More)
We have collected a database of musical features from radio broadcasts and CD collections (N &gt; 10<sup>5</sup>). The database poses a number of hard modelling challenges including: Segmentation problems and missing and wrong meta-data. We describe our efforts towards cleaning the data using probability density estimation. We train conditional densities(More)