Download Blackboard system and top-down processing for the transcription of simple polyphonic music
A system is proposed to perform the automatic music transcription of simple polyphonic tracks using top-down processing. It is composed of a blackboard system of three hierarchical levels, receiving its input from a segmentation routine in the form of an averaged STFT matrix. The blackboard contains a hypotheses database, a scheduler and knowledge sources, one of which is a neural network chord recogniser with the ability to reconfigure the operation of the system, allowing it to output more than one note hypothesis at a time. The basic implementation is explained, and some examples are provided to illustrate the performance of the system. The weaknesses of the current implementation are shown and next steps for further development of the system are defined.
Download Complex domain onset detection for musical signals
We present a novel method for onset detection in musical signals. It improves over previous energy-based and phase-based approaches by combining both types of information in the complex domain. It generates a detection function that is sharp at the position of onsets and smooth everywhere else. Results on a handlabelled data-set show that high detection rates can be achieved at very low error rates. The approach is more robust than its predecessors both theoretically and practically.
Download A comparison Between Fixed and Multiresolution Analysis for Onset Detection in Musical Signals
A study is presented for the use of multiresolution analysis-based onset detection in the complex domain. It shows that using variable time-resolution across frequency bands generates sharper detection functions for higher bands and more accurate detection functions for lower bands. The resulting method improves the localisation of onsets on fixed-resolution schemes, by favouring the increased time precision of higher subbands during the combination of results.
Download Fast implementation for non-linear time-scaling of stereo signals
In this paper we present an improved implementation of Duxbury’s adaptive phase-vocoder approach for audio time-stretching using non-linear time-scaling and temporal masked phase locking at transients . We show that the previous algorithm has some limitations, notably its slow implementation and its incapacity to deal with stereo signals. We propose solutions to this problems including: an improved transient detection, a much faster implementation using the IFFT for re-synthesis and a method for stretching stereo signals without artifacts. Finally, we provide some graphical results and quantitative measures to illustrate our improvements.