From Local to Global Analysis of Music Time Series

Local and more and more global musical structure is analyzed from audio time series by time-series-event analysis with the aim of automatic sheet music production and comparison of singers. Note events are determined and classified based on local spectra, and rules of bar events are identified based on accentuation events related to local energy. In order to compare the performances of different singers global summary measures are defined characterizing the overall performance. --

scatterplot3d - An R Package for Visualizing Multivariate Data

Scatterplot3d is an R package for the visualization of multivariate data in a three dimensional space. R is a "language for data analysis and graphics". In this paper we discuss the features of the package. It is designed by exclusively making use of already existing functions of R and its graphics system and thus shows the extensibility of the R graphics system. Additionally some examples on generated and real world data are provided.

Parameter Optimization in Automatic Transcription of Music

Based on former work on automatic transcription of musical time series into sheet music (Ligges et al. (2002), Weihs and Ligges (2003, 2005)) in this paper parameters of the transcription algorithm are optimized for various real singers. Moreover, the parameters of various artificial singer models derived from the models of Rossignol et al. (1999) and Davy and Godsill (2002) are estimated. In both cases, optimization is carried out by the Nelder-Mead (1965) search algorithm. In the modelling case a hierarchical Bayes extension is estimated by WinBUGS (Spiegelhalter et al. (2004)) as well. In all cases, optimal parameters are compared to heuristic estimates from our former standard method. --

Prospects and Challenges in R Package Development

R, a software package for statistical computing and graphics, has evolved into the lingua franca of (computational) statistics. One of the cornerstones of R's success is the decentralized and modularized way of creating software using a multi-tiered development model: The R Development Core Team provides the "base system", which delivers basic statistical functionality, and many other developers contribute code in the form of extensions in a standardized format via so-called packages. In order to be accessible by a broader audience, packages are made available via standardized source code repositories. To support such a loosely coupled development model, repositories should be able to verify that the provided packages meet certain formal quality criteria and "work": both relative to the development of the base R system as well as with other packages (interoperability). However, established quality assurance systems and collaborative infrastructures typically face several challenges, some of which we will discuss in this paper.Series: Research Report Series / Department of Statistics and Mathematic

Register Classification by Timbre

The aim of this analysis is the demonstration that the high and the low musical register (Soprano, Alto vs. Tenor, Bass) can be identified by timbre, i.e. after pitch information is eliminated from the spectrum. This is achieved by means of pitch free characteristics of spectral densities of voices and instruments, namely by means of masses and widths of peaks of the first 13 partials (cp. Weihs and Ligges (2003b)). Different analyses based on the tones in the classical song ?Tochter Zion? composed by G.F. Händel are presented. Results are very promising. E.g., if the characteristics are averaged over all tones, then female and male singers can be easily distinguished without any error (prediction error of 0%)! Moreover, stepwise linear discriminant analysis can be used to separate even the females together with 28 high instruments (?playing? the Alto version of the song) from the males together with 20 low instruments (playing the Bass version) with a prediction error of 4%. Also, individual tones are analysed, and the statistical results are discussed and interpreted from acoustics point of view. --

R2WinBUGS: A Package for Running WinBUGS from R

The R2WinBUGS package provides convenient functions to call WinBUGS from R. It automatically writes the data and scripts in a format readable by WinBUGS for processing in batch mode, which is possible since version 1.4. After the WinBUGS process has finished, it is possible either to read the resulting data into R by the package itself--which gives a compact graphical summary of inference and convergence diagnostics--or to use the facilities of the coda package for further analyses of the output. Examples are given to demonstrate the usage of this package.

In Search of Variables Distinguishing Low and High Achievers in Music Sight Reading Task

The unrehearsed performance of music, called ?sight reading? (SR), is a basic skill for all musicians. Despite the merits of expertise theory, there is no comprehensive model which can classify subjects into high and low performance groups. This study is the first that classifies subjects and is based on an extensive experiment measuring the total SR performance of 52 piano students. Classification methods (cluster analysis, classification tree, linear discriminant analysis) were applied. Results of a linear discriminant analysis revealed a 2-class solution with 4 predictors (predictive error: 15%). --

Online Linear Discriminant Analysis for Data Streams with Concept Drift

Various methods based on classical classification methods such as linear discriminant analysis (LDA) have been developed for working on data streams in situations with concept drift. Nevertheless, the updated classifiers of such methods may result in a bad prediction error rate in case the underlying distribution incrementally changes further on. Therefore, we invented a rather general extension to such methods to improve the forecasting quality. Under some assumptions we estimate a model for the time-dependent concept drift that is used to predict the forthcoming distributions of the features. These predictions of distributions are finally used in the LDA to build the classification rule and hence for predicting new observations. In a simulation study we consider different kinds of concept drift and compare the new extended methods with the methods these are based on