Download Low-Cost Geometry-Based Acoustic Rendering In this paper we propose a new sound rendering algorithm that allows the listener to move within a dinamic acoustic environment. The main goal of this work is to implement a real-time sound rendering software for Virtal Reality applications, which runs on lowcost platforms. The resulting numeric structure is a recursive filter able to efficiently simulate the impulse response of a large room.
Download Sound spatialization based on fast beam tracing in the dual space This paper addresses the problem of geometry-based sound reverberation for applications of virtual acoustics. In particular, we propose a novel method that allows us to significantly speed-up the construction of the beam tree in beam tracing applications, by avoiding space subdivision. This allows us to dynamically recompute the beam tree as the sound source moves. In order to speedup the construction of the beam tree, we determine what portion of which reflectors the beam “illuminates” by performing visibility checks in the “dual” of the geometric space.
Download Automatic synthesis strategies for object-based dynamical physical models in musical acoustics Current physics-based synthesis techniques tend to synthesize the interaction between different functional elements of a sound generator by treating it as a single system. However, when dealing with the physical modeling of complex sound generators this choice raises questions about the resulting flexibility of the adopted synthesis strategy. One way to overcome this problem is to approach it by individually synthesizing and discretizing the objects that contribute to the generation of sounds. In this paper we address the problem of how to automatize the process of physically modeling the interaction between objects, and how to make it dynamical. We will show that this can be done through the automatic definition and implementation of a topology model that adapts to the contact and proximity conditions between the considered objects.
Download Real Time Modeling of Acoustic Propagation in Complex Environments In order to achieve high-quality audio-realistic rendering in complex environments, we need to determine all the acoustic paths that go from sources to receivers, due to specular reflections as well as diffraction phenomena. In this paper we propose a novel method for computing and auralizing the reflected as well as the diffracted field in 2.5D environments. The method is based on a preliminary geometric analysis of the mutual visibility of the environment reflectors. This allows us to compute on the fly all possible acoustic paths, as the information on sources and receivers becomes available. The construction of a beam tree, in fact, is here performed through a look-up of visibility information and the determination of acoustic paths is based on a lookup on the computed beam tree. We also show how to model diffraction using the same beam tree structure used for modeling reflection and transmission. In order to validate the method we conducted an acquisition campaign over a real environment and compared the results obtained with our real-time simulation system.
Download Non-Linear Digital Implementation of a Parametric Analog Tube Ground Cathode Amplifier In this paper we propose a digital simulation of an analog amplifier circuit based on a grounded-cathode amplifier with parametric tube model. The time-domain solution enables the online valve model substitution and zero-latency changes in polarization parameters. The implementation also allows the user to match various types of tube processing features.
Download Rendering of an acoustic beam through an array of loudspeakers This paper addresses the problem of rendering a virtual source through loudspeaker arrays. The orientation of the virtual source and its aperture determine its radial beampattern. The methodology we present here imposes that the wavefield in a predetermined listening area best approximates the desired wavefield in the least squares sense. With respect to the traditional techniques the number of constraints is much higher than the number of loudspeakers. As a consequence, the loudspeaker coefficient vector is the solution of an over-determined equation system. Moreover this system may be ill-conditioned. In order to solve these issues, we resort to a least squares inversion combined with a Singular Value Decomposition (SVD) to attenuate the problem of ill-conditioning. Some experimental results show the feasibility and the issues of this methodology.
Download Music Genre visualization and Classification Exploiting a Small set of High-level Semantic Features In this paper a system for continuous analysis, visualization and classification of musical streams is proposed. The system performs visualization and classification task by means of three high-level, semantic features extracted computing a reduction on a multidimensional low-level feature vector through the usage of Gaussian Mixture Models. The visualization of the semantic characteristics of the audio stream has been implemented by mapping the value of the high-level features on a triangular plot and by assigning to each feature a primary color. In this manner, besides having the representation of musical evolution of the signal, we have also obtained representative colors for each musical part of the analyzed streams. The classification exploits a set of one-against-one threedimensional Support Vector Machines trained on some target genres. The obtained results on visualization and classification tasks are very encouraging: our tests on heterogeneous genre streams have shown the validity of proposed approach.
Download Drum Music Transcription Using Prior Subspace Analysis and Pattern Recognition Polyphonic music transcription has been an active field of research for several decades, with significant progress in past few years. In the specific case of automatic drum music transcription, several approaches have been proposed, some of which based on feature analysis, source separation and template matching. In this paper we propose an approach that incorporates some simple rules of music theory with the goal of improving the performance of conventional low-level drum transcription methods. In particular, we use Prior Subspace Analysis for early drum transcription, and we statistically process its output in order to recognize drum patterns and perform error correction. Experiments on polyphonic popular recordings showed that the proposed method improved the transcription accuracy of the original transcription results from 75% to over 90%.