Download Spatial audio quality and user preference of listening systems in video games
Spatial audio playback solutions provide video game players with ways to experience more immersive and engaging video game content. This paper aims to find whether listening systems that are able to more accurately convey spatial information are preferred by video game players, and to what extent this is true for different loudspeaker configurations whilst engaged in video game play. Results do suggest that a listening system with high perceived spatial quality is more preferred.
Download Frequency estimation of the first pinna notch in Head-Related Transfer Functions with a linear anthropometric model
The relation between anthropometric parameters and Head-Related Transfer Function (HRTF) features, especially those due to the pinna, are not fully understood yet. In this paper we apply signal processing techniques to extract the frequencies of the main pinna notches (known as N1 , N2 , and N3 ) in the frontal part of the median plane and build a model relating them to 13 different anthropometric parameters of the pinna, some of which depend on the elevation angle of the sound source. Results show that while the considered anthropometric parameters are not able to approximate with sufficient accuracy neither the N2 nor the N3 frequency, eight of them are sufficient for modeling the frequency of N1 within a psychoacoustically acceptable margin of error. In particular, distances between the ear canal and the outer helix border are the most important parameters for predicting N1 .
Download Relative auditory distance discrimination with virtual nearby sound sources
In this paper a psychophysical experiment targeted at exploring relative distance discrimination thresholds with binaurally rendered virtual sound sources in the near field is described. Pairs of virtual sources are spatialized around 6 different spatial locations (2 directions ×3 reference distances) through a set of generic far-field Head-Related Transfer Functions (HRTFs) coupled with a nearfield correction model proposed in the literature, known as DVF (Distance Variation Function). Individual discrimination thresholds for each spatial location and for each of the two orders of presentation of stimuli (approaching or receding) are calculated on 20 subjects through an adaptive procedure. Results show that thresholds are higher than those reported in the literature for real sound sources, and that approaching and receding stimuli behave differently. In particular, when the virtual source is close (< 25 cm) thresholds for the approaching condition are significantly lower compared to thresholds for the receding condition, while the opposite behaviour appears for greater distances (≈ 1 m). We hypothesize such an asymmetric bias to be due to variations in the absolute stimulus level.
Download Block-oriented modeling of distortion audio effects using iterative minimization
Virtual analog modeling is the process of digitally recreating an analog device. This study focuses on analog distortion pedals for guitarists, which are categorized as stompboxes, because the musician turns them on and off by stepping on the switch. While some of the current digital models of distortion effects are circuit-based, this study uses a signal-based approach to identify the device under test (DUT). An algorithm to identify any distortion effect pedal in any given setting by input-output (I/O) measurements is proposed. A parametric block-oriented Wiener-Hammerstein model for distortion effects and the corresponding iterative error minimization procedure are introduced. The algorithm is implemented in Matlab and uses the Levenberg-Marquardt minimization procedure with boundaries for the parameters.
Download Approximating non-linear inductors using time-variant linear filters
In this paper we present an approach to modeling the non-linearities of analog electronic components using time-variant digital linear filters. The filter coefficients are computed at every sample depending on the current state of the system. With this technique we are able to accurately model an analog filter including a nonlinear inductor with a saturating core. The value of the magnetic permeability of a magnetic core changes according to its magnetic flux and this, in turn, affects the inductance value. The cutoff frequency of the filter can thus be seen as if it is being modulated by the magnetic flux of the core. In comparison to a reference nonlinear model, the proposed approach has a lower computational cost while providing a reasonably small error.
Download Digitizing the Ibanez Weeping Demon Wah Pedal
Being able to transform an analog audio circuit into a digital model is a big deal for musicians, producers, and circuit benders alike. In this paper, we address some of the issues that arise when attempting to make such a digital model. Using the canonical state variable filter as the main point of interest in our schematic, we will walk through the process of making a signal flow graph, obtaining a transfer function, and making a usable digital filter. Additionally, we will address an issue that is common throughout virtual analog literature; reducing the very large expressions for each of the filter coefficients. Using a novel factoring algorithm, we show that these expressions can be reduced from thousands of operations down to tens of operations.
Download Cascaded prediction in ADPCM codec structures
The aim of this study is to demonstrate how ADPCM-based codec structures can be improved using cascaded prediction. The advantage of predictor cascades is to allow the adaption to several signal conditions, as it is done in block-based perceptual codecs like MP3, AAC, etc. In other words, additional predictors with a small order are supposed to enhance the prediction of non-stationary signals. The predictor cascade is complemented with a simple adaptive quantizer to yield a simple exemplary codec which is used to demonstrate the influence of the predictor cascade. Several cascade configurations are considered and optimized using a genetic algorithm. A measurement of the prediction gain and the ODG score utilizing the PEAQ algorithm applied to the SQAM dataset shall reveal the potential improvements.
Download Beat histogram features for rhythm-based musical genre classification using multiple novelty functions
In this paper we present beat histogram features for multiple level rhythm description and evaluate them in a musical genre classification task. Audio features pertaining to various musical content categories and their related novelty functions are extracted as a basis for the creation of beat histograms. The proposed features capture not only amplitude, but also tonal and general spectral changes in the signal, aiming to represent as much rhythmic information as possible. The most and least informative features are identified through feature selection methods and are then tested using Support Vector Machines on five genre datasets concerning classification accuracy against a baseline feature set. Results show that the presented features provide comparable classification accuracy with respect to other genre classification approaches using periodicity histograms and display a performance close to that of much more elaborate up-to-date approaches for rhythm description. The use of bar boundary annotations for the texture frames has provided an improvement for the dance-oriented Ballroom dataset. The comparably small number of descriptors and the possibility of evaluating the influence of specific signal components to the general rhythmic content encourage the further use of the method in rhythm description tasks.
Download An Evaluation of Audio Feature Extraction Toolboxes
Audio feature extraction underpins a massive proportion of audio processing, music information retrieval, audio effect design and audio synthesis. Design, analysis, synthesis and evaluation often rely on audio features, but there are a large and diverse range of feature extraction tools presented to the community. An evaluation of existing audio feature extraction libraries was undertaken. Ten libraries and toolboxes were evaluated with the Cranfield Model for evaluation of information retrieval systems, reviewing the coverage, effort, presentation and time lag of a system. Comparisons are undertaken of these tools and example use cases are presented as to when toolboxes are most suitable. This paper allows a software engineer or researcher to quickly and easily select a suitable audio feature extraction toolbox.
Download Digitally Moving An Electric Guitar Pickup
This paper describes a technique to transform the sound of an arbitrarily selected magnetic pickup into another pickup selection on the same electric guitar. This is a first step towards replicating an arbitrary electric guitar timbre in an audio recording using the signal from another guitar as input. We record 1458 individual notes from the pickups of a single guitar, varying the string, fret, plucking position, and dynamics of the tones in order to create a controlled dataset for training and testing our approach. Given an input signal and a target signal, a least squares estimator is used to obtain the coefficients of a finite impulse response (FIR) filter to match the desired magnetic pickup position. We use spectral difference to measure the error of the emulation, and test the effects of independent variables fret, dynamics, plucking position and repetition on the accuracy. A small reduction in accuracy was observed for different repetitions; moderate errors arose when the playing style (plucking position and dynamics) were varied; and there were large differences between output and target when the training and test data comprised different notes (fret positions). We explain results in terms of the acoustics of the vibrating strings.