Download Separation of Musical Instruments based on Perceptual and Statistical Principles The separation of musical instruments acoustically mixed in one source is a very active field which has been approached from many different viewpoints. This article compares the blind source separation perspective and oscillatory correlation theory taking the auditory scene analysis as the point of departure (ASA). The former technique deals with the separation of a particular signal from a mixture with many others from a statistical point of view. Through the standard Independent Component Analysis (ICA), a blind source separation can be done using the particular and the mixed signals' statistical properties. Thus, the technique is general and does not use previous knowledge about musical instruments. In the second approach, an ASA extension is studied with a dynamic neural model which is able to separate the different musical instruments taking a priori unknown perceptual elements as a point of departure. Applying an inverse transformation to the output of the model, the different contributions to the mixture can be recovered again in the time domain.
Download New techniques and Effects in Model-based Sound Synthesis Physical modeling and model-based sound synthesis have recently been among the most active topics of computer music and audio research. In the modeling approach one typically tries to simulate and duplicate the most prominent sound generation properties of the acoustic musical instrument under study. If desired, the models developed may then be modified in order to create sounds that are not common or even possible from physically realizable instruments. In addition to physically related principles it is possible to combine physical models with other synthesis and signal processing methods to realize hybrid modeling techniques.
This article is written as an overview of some recent results in model-based sound synthesis and related signal processing techniques. The focus is on modeling and synthesizing plucked string sounds, although the techniques may find much more widespread application. First, as a background, an advanced linear model of the acoustic guitar is discussed along with model control principles. Then the methodology to include inherent nonlinearities and time-varying features is introduced. Examples of string instrument nonlinearities are studied in the context of two specific instruments, the kantele and the tanbur, which exhibit interesting nonlinear effects.
Download Radial Basis Function Networks for conversion of sound spectra In many high-level signal processing tasks, such as pitch shifting, voice conversion or sound synthesis, accurate spectral processing is required. Here, the use of Radial Basis Function Networks (RBFN) is proposed for the modeling of the spectral changes (or conversions) related to the control of important sound parameters, such as pitch or intensity. The identification of such conversion functions is based on a procedure which learns the shape of the conversion from few couples of target spectra from a data set. The generalization properties of RBFNs provides for interpolation with respect to the pitch range. In the construction of the training set, mel-cepstral encoding of the spectrum is used to catch the perceptually most relevant spectral changes. The RBFN conversion functions introduced are characterized by a perceptually-based fast training procedure, desirable interpolation properties and computational efficiency.
Download Time-domain model of the singing voice A combined physical model for the human vocal folds and vocal tract is presented. The vocal fold model is based on a symmetrical 16 mass model by Titze. Each vocal fold is modeled with 8 masses that represent the mucosal membrane coupled by non-linear springs to another 8 masses for the vocalis muscle together with the ligament. Iteratively, the value of the glottal flow is calculated and taken as input for calculation of the aerodynamic forces. Together with the spring forces and damping forces they yield the new positions of the masses that are then used for the calculation of a new glottal flow value. The vocal tract model consists of a number of uniform cylinders of fixed length. At each discontinuity incident, reflected and transmitted waves are calculated including damping. Assuming a linear system, the pressure signal generated by the vocal fold model is either convoluted with the Green’s function calculated by the vocal tract model or calculated interactively assuming variable reflection coefficients for the glottis and the vocal tract during phonation. The algorithms aim at real-time performance and are implemented in MATLAB.
Download Symbolic and audio processing to change the expressive intention of a recorded music performance A framework for real-time expressive modification of audio musical performances is presented. An expressiveness model compute the deviations of the musical parameters which are relevant in terms of control of the expressive intention. The modifications are then realized by the integration of the model with a sound processing engine.