: We wanl lo creale a working 1001 for malhematics leachers and a corresponding learning 1001 for sludenls, namely a graphical simulalor of malhemalical algorilhms (GraSMa). To achieve il we Iry Iwo differenl slralegies. We slarled by annolaling manually lhe original algorilhm wilh inspeclor functions. Now we are lesting a new approach Ihal aims ai aulomalically annolaling lhe original code wilh inspeclor funclions. To achieve Ihis we are developing a language Iranslalor module Ihal enables us lo commenl aulomatically on any code written in Oclave language. The run of lhe annolaled code galed by one of Ihese two ways, records in a XML (eXlensible Markup Language) file everylhing Ihal happened during lhe execution. Subsequentiy, lhe XML file is parsed by a Java applicalion Ihal graphically represenls lhe malhemalic objecls and Iheir behaviour during execulion. The final application will be accessed on-line Ihrough a websile (WebGraSMa) which is currentiy under developmenl. In Ihis paper we reporl and discuss aboul lhe procedures followed and presenl some intermediate results.
: The traditional pitch histogram and various features extracted from it play a pivotal role in music information retrieval. In the research on songs, especially applying pitch statistics to investigate the main melody, we found that the pitch histogram may not necessarily reflect the notes’ pitch characteristic of the whole song perfectly. Therefore, we took the note duration into account to propose two advanced versions of pitch histograms and validated their applicability. This paper introduces these two novel histograms: the merged pitch histogram by merging consecutively repeated pitches and the pitch-duration histogram by utilizing each pitch’s duration information. Complemented by the description of their calculation algorithms, the discussion of their advantages and limitations, the analysis of their application to songs from various languages and cultures, and the demonstration of their use cases in state-of-the-art research works, the proposed histograms’ characteristics and usefulness are intuitively revealed.
In this paper we propose spline models of audio as the first step toward a hierarchical system of level of detail (LOD) for audio rendering. We describe methods such as cycle interpolation which can produce spline models and approximations of audio data. These models can be used to render output in realtime, but can also be mixed prior to rendering. Examples of audio data simplified to spline models with cycle interpolation can reduce the data to less than 2% of the full resolution data size, with only minor impact to audio quality. We present a sequence of such examples with instrument models. We also introduce the idea of pre-rendered filtering and mixing, based on the B-spline coefficients of the models.
