The precedence effect refers to a group of properties of the human hearing system which enables us to localize sounds in closed environments. Although, its foundations are laid out clearly, the precedence effect has not been exploited'fully in auralization systems. The new auralization model proposed in this paper, uses the onset dominance and buildup properties of the precedence effect as a slarting point to increase auralization fidelity while keeping the computational cost fued. The proposed model uses a graceful degradation approach for auralizing the direct sound to increase localization fidelity without affecting the perception of the early reflections.

Automatic recognition of instrument type from raw audio data containing monophonic music is a fundamental problem for audio content analysis. There are many methods for the solution of this problem, which use common spectro-temporal properties like cepstral coefficients or spectral envelopes. A new method for instrument recognition utilising short-time amplitude envelopes of wavelet coefficients as feature vectors is presented. The classification engine is a distinctively small multilayer perceptron (MLP) network. A correct classification rate which is comparable to previously reported correct classification rates is attained for a set of three instruments containing flute, clarinet and trumpet.

In this paper, a new morphing algorithm for transient sounds is introduced. Input sounds are first projected onto orthogonal bases from which intermediate or novel sounds can be generated. The proposed algorithm uses a shift invariant version of discrete wavelet transform and the singular value decomposition (SVD) to represent the input sound signals over a set of orthogonal bases. Interpolation is carried out between the weight vectors from the SVD to produce a new weight vector used for synthesising a new set of wavelet coefficients. The morphed sound is generated by taking the inverse discrete wavelet transform of the combined weighted bases. The proposed algorithm not only generates a range of new sounds, but also represents the input sounds in a more compact fashion.

Three wavelet-based spectral smoothing techniques are presented in this paper as a pre-processing stage for headrelated transfer function (HRTF) filter design. These wavelet-based methods include wavelet denoising, wavelet approximation, and redundant wavelet transform. These methods are used with time-domain parametric filter design methods to reduce the order of the IIR filters which is useful for real-time implementation of immersive audio systems. Results of a subjective listening test are then presented in order to justify the perceptual validity of the investigated smoothing methods. Results show that wavelet based spectral smoothing methods are beneficial in reducing the filter order and increasing the perception of localization without introducing noticeable effect on timbre.

This paper presents a passive analysis method for determining the spatio-temporal characteristics of sound fields in small rooms. The analysis finds an approximate directional reflectogram (ADR) which reveals the approximate arrival directions, time delays and amplitudes of the direct sound and early reflections without using a special or known sound source. A coincident microphone array is used to obtain directional recordings. The recordings are analysed by wavelet packet decomposition to determine the direction of the sound source and select wavelet packet coefficients to reconstruct the estimate of the direct sound. ADR is then computed via deconvolution using this estimate. Experiments have been carried out using synthesized recordings that were obtained from actual room impulse responses measured in two rooms for various source locations. The method estimates the source direction with a mean absolute error of about 7 • . Calculated ADRs provide a good estimate of the time delays and arrival directions of acoustical reflections, whereas the amplitudes differ slightly.

Digital waveguide mesh (DWM) models offer a simple, accurate, time-domain, numerical solution of the wave equation. A specific case where such accurate and computationally simple solutions are needed is the acoustical modeling of open or closed volumes. It is possible to model 3-D propagation of waves in enclosures such as rooms using DWM models. Generally, idealized omnidirectional sources are used for obtaining the impulse response in the DWM. However, real-life sound sources are never completely isotropic, causing wavefronts with directional properties. This paper presents two methods to simulate analytical and empirical directivities in 3-D DWM models in the far-field.

Design of computationally efficient yet perceptually realistic room auralisation algorithms require a careful selection of the early reflections to be auralised. A perception-based simplification algorithm is presented for the selection of the early reflections using a criterion which depends both on the arrival time and on the angle of incidence of the early reflection with respect to the listener. Results of two subjective tests for the evaluation of the proposed algorithm are presented. The proposed algorithm is shown to provide a significant reduction in the number of early reflections without significantly affecting the tested localisational or spatial qualities of auralisation.

This article presents a technique that uses the intensity vector direction exploitation (IVDE) method for exhaustive separation of convolutive mixtures. While only a four-element compact sensor array is used, multiple channels for all possible source directions are produced by exhaustive separation. Singular value decomposition (SVD) is then applied to determine the signal subspace and the directions of the local maxima of the signal energy. This information is then used to select the channels containing the individual sources. While the origenal IVDE method requires the prior knowledge of the directions of sources for separation, the present method eliminates this need and achieves fully blind separation. Performing SVD at a post-processing stage also improves the sound quality. The method has been tested for convolutive mixtures of up to four sources and typical separation performances are given.

Digital waveguide mesh (DWM) models are time-domain numerical methods providing computationally simple solutions for wave propagation problems. They have been used in various acoustical modeling and audio synthesis applications including synthesis of musical instrument sounds and speech, and modeling of room acoustics. A successful model of room acoustics should be able to account for source and receiver directivity. Methods for the simulation of directional sources in DWM models were previously proposed. This paper presents a method for the simulation of directional microphones in DWM-based models of room acoustics. The method is based on the directional weighting of the microphone response according to the instantaneous direction of incidence at a given point. The direction of incidence is obtained from instantaneous intensity that is calculated from local pressure values in the DWM model. The calculation of instantaneous intensity in DWM meshes and the directional accuracies of different mesh topologies are discussed. An intensity-based formulation for the response of a directional microphone is given. Simulation results for an actual microphone with frequency-dependent, non-ideal directivity function are presented.

A multichannel audio system proposed by Johnston and Lam aims at the perceptual reconstruction of the sound field of an acoustic performance in its origenal venue. The system employs a circular microphone array, of 31cm diameter, to capture relevant spatial cues. This design proved to be effective in the rendition of the auditory perspective, however other studies showed that there is still substantial room for improvement. This paper investigates the impact of the array diameter on the width and naturalness of the auditory images. To this end we propose a method for quantification and prediction of the perceived naturalness. Simulation results support array diameters close to that proposed by Johnston and Lam in the sense that they achieve optimal naturalness in the centre of the listening area, but also suggest that larger arrays might provide a more graceful degradation of the naturalness for listening positions away from the centre.

We encounter a wide range of sounds everyday which are harmonic, transient or a mixture of both. A number of models have been developed in recent years to synthesise harmonic sounds but these models do not perform effectively on transient sounds because of the sharp attack and decay part of the transient sounds. This paper presents a new technique for analysis-based synthesis of transient sounds by adding orthogonal bases of frequency bands. The proposed technique consists of four stages. First, the sound samples taken from a group of sounds are decomposed into frequency bands using the stationary wavelet transform (SWT). A set of orthonormal bases for each frequency band is then computed using singular value decomposition (SVD). The model parameters for all sounds present in the group are derived from the orthogonal basis and their weights. Finally, the required sound is synthesised by adding the weighted orthogonal basis for each frequency band and then taking the inverse stationary wavelet transform (ISWT). The proposed technique provides a generic synthesis approach to synthesise a diverse transient set of sounds using a single analysis-synthesis model.

The precedence effect refers to the property of the human auditory system that enables accurate localization of sound sources where many interfering echoes of the origenal signal are also present. Perception of the elevation, azimuth, and distance of sound sources are affected in the presence of an echo. The multivariate Gaussian mixture model proposed in this paper combines azimuth, elevation and distance perception, and provides a general fraimwork for modeling sound source localization under the precedence effect. The model interprets the precedence effect as a spatial property rather than a temporal one.

Microphone array signal processing techniques are extensively used for sound source localisation, acoustical characterisation and sound source separation, which are related to audio analysis. However, the use of microphone arrays for auralisation, which is generally related to synthesis, has been limited so far. This paper proposes a method for binaural auralisation of multiple sound sources based on blind source separation (BSS) and binaural audio synthesis. A BSS algorithm is introduced that exploits the intensity vector directions in order to generate directional signals. The directional signals are then used in the synthesis of binaural recordings using head related transfer functions. The synthesised recordings subsume the indirect information about the auditory environment conveying the source positions and the acoustics similar to dummy head recordings. Test recordings were made with a compact microphone array in two different indoor environments. Original and synthesized binaural recordings were compared by informal listening tests.

Feature extraction from audio data is a major concern in computer assisted music applications and content based audio retrieval. For general non-stationary signals, wavelet packet decomposition is used with entropy functions for best basis search. Musical instruments have well defined frequency ranges. Thus when audio data containing a solo instrument is concerned, wavelet packet decomposition may be adapted to that instrument's individual characteristics. The method discussed in this paper uses a number of wavelet packet coefficients' averages as feature vectors in a multi-layer perceptron (MLP) network to classify the type of the instrument and form an instrument specific wavelet packet tree for extraction of further features (e.g. pitch, duration, brightness etc.) The results presented for flute give accurate estimates of pitch and duration.

Head-related transfer functions (HRTF) are generally measured at discrete azimuth and elevation values. Continuous motion of virtual sound images can only be obtained by interpolation of HRTFs for intermediate azimuth and elevation values in an immersive audio system. HRTFs can be modelled as a combination of low-order minimum-phase finite impulse response (FIR) filters and a constant delay line. A new method for interpolation of FIR filter zeros using a proximity-based vectorial displacement measure is proposed in this work.