Download Source Filter Model For Expressive Gu-Qin Synthesis and its iOS App
Gu-Qin as a venerable Chinese plucked-string instrument has its unique performance techniques and enchanting sounds. It is on the UNESCO Representative List of the Intangible Cultural Heritage of Humanity. It is one of the oldest Chinese solo instruments. The variation of Gu-Qin sound is so large that carefullydesigned controls of its computer synthesizer are necessary. We developed a parametric source-filter model for re-synthesizing expressive Gu-Qin notes. It is capable to cover as many as possible combinations of Gu-Qin’s performance techniques. In this paper, a brief discussion of Gu-Qin playing and its special tablature notation are made for understanding the relationship between its performance techniques and its sounds. This work includes a Gu-Qin’s musical notation system and a source-filter model based synthesizer. In addition, we implement an iOS app to demonstrate its low computation complexity and robustness. It is easy to perform improvisation of the sounds because of its friendly user interfaces.
Download TELTPC Based Re-Synthesis Method for Isolated Notes of Polyphonic Instrumental Music Recordings
In this paper, we presented a flexible analysis/re-synthesis method for smoothly changing the properties of isolated notes in polyphonic instrumental music recordings. True Envelope Linear Predictive Coding (TELPC) method has been employed as the analysis/synthesis model in order to preserve the original timbre quality as much as possible due to its accurate spectral envelope estimation. We modified the conventional LPC analysis/synthesis processing by using pitch synchronous analysis frames to avoid the severe magnitude modulation problem. Smaller frames can thus be used to capture more local characteristics of the original signals to further improve the sound quality. In this framework, one can manipulate a sequence of isolated notes from two commercially available polyphonic instrumental music recordings and interesting re-synthesized results are achieved.
Download Timbre-Constrained Recursive Time-Varying Analysis for Musical Note Separation
Note separation in music signal processing becomes difficult when there are overlapping partials from co-existing notes produced by either the same or different musical instruments. In order to deal with this problem, it is necessary to involve certain invariant features of musical instrument sounds into the separation processing. For example, the timbre of a note of a musical instrument may be used as one possible invariant feature. In this paper, a timbre estimate is used to represent this feature such that it becomes a constraint when note separation is performed on a mixture signal. To demonstrate the proposed method, a timedependent recursive regularization analysis is employed. Spectral envelopes of different notes are estimated and a modified parameter update strategy is applied to the recursive regularization process. The experiment results show that the flaws due to the overlapping partial problem can be effectively reduced through the proposed approach.