Download First-Order Ambisonic Coding with PCA Matrixing and Quaternion-Based Interpolation We present a spatial audio coding method which can extend existing speech/audio codecs, such as EVS or Opus, to represent first-order ambisonic (FOA) signals at low bit rates. The proposed method is based on principal component analysis (PCA) to decorrelate ambisonic components prior to multi-mono coding. The PCA rotation matrices are quantized in the generalized Euler angle domain; they are interpolated in quaternion domain to avoid discontinuities between successive signal blocks. We also describe an adaptive bit allocation algorithm for an optimized multi-mono coding of principal components. A subjective evaluation using the MUSHRA methodology is presented to compare the performance of the proposed method with naive multi-mono coding using a fixed bit allocation. Results show significant quality improvements at bit rates in the range of 52.8 kbit/s (4 × 13.2) to 97.6 kbit/s (4 × 24.4) using the EVS codec.
Download Bio-Inspired Optimization of Parametric Onset Detectors Onset detectors are used to recognize the beginning of musical
events in audio signals. Manual parameter tuning for onset detectors is a time consuming task, while existing automated approaches often maximize only a single performance metric. These
automated approaches cannot be used to optimize detector algorithms for complex scenarios, such as real-time onset detection
where an optimization process must consider both detection accuracy and latency. For this reason, a flexible optimization algorithm
should account for more than one performance metric in a multiobjective manner. This paper presents a generalized procedure for
automated optimization of parametric onset detectors. Our procedure employs a bio-inspired evolutionary computation algorithm
to replace manual parameter tuning, followed by the computation
of the Pareto frontier for multi-objective optimization. The proposed approach was evaluated on all the onset detection methods
of the Aubio library, using a dataset of monophonic acoustic guitar
recordings. Results show that the proposed solution is effective in
reducing the human effort required in the optimization process: it
replaced more than two days of manual parameter tuning with 13
hours and 34 minutes of automated computation. Moreover, the
resulting performance was comparable to that obtained by manual
optimization.
Download Arbitrary Polygon Oscillator: Generalizing Polygonal Synthesis to Arbitrary Shapes, Morphing, and Three-Dimensional Polyhedra Polygonal synthesis generates audio by traversing the perimeter of a polygon with a phasor; prior work uses a constant angular velocity, whereas the proposed system adopts constant arc-length (perimeter) velocity. Existing formulations operate on regular, parametrically defined polygons, producing smooth timbral transitions within a single family of shapes. This paper generalizes polygonal synthesis around a unified arc-length engine: vertex data of any origin feed the same DSP pipeline. First, we adapt the oscillator to accept arbitrary vertex configurations from an external buffer, opening the possibility for a broad class of closed polygons — regular, irregular, or star-shaped — to function as a waveform generator. Second, a hybrid interpolation algorithm enables smooth morphing between polygons with unequal vertex counts, passing through intermediate shapes that have no parametric description. Third, we extend the paradigm to three dimensions: a convex polyhedron rotated about three axes is sliced by a fixed horizontal plane, and the resulting cross-section yields a continuously variable polygon controlled by the solid's orientation. The system runs in RNBO (Cycling '74) with a geometry caching strategy that avoids per-sample recomputation. Antialiasing combines a four-point polyBLAMP correction derived from runtime Bézier tangents with adaptive oversampling, adapting the correction geometrically to general vertex configurations without per-shape analytical derivation.
Download Sinusoid Extraction and Salience Function Design for Predominant Melody Estimation In this paper we evaluate some of the alternative methods commonly applied in the first stages of the signal processing chain of automatic melody extraction systems. Namely, the first two stages are studied – the extraction of sinusoidal components and the computation of a time-pitch salience function, with the goal of determining the benefits and caveats of each approach under the specific context of predominant melody estimation. The approaches are evaluated on a data-set of polyphonic music containing several musical genres with different singing/playing styles, using metrics specifically designed for measuring the usefulness of each step for melody extraction. The results suggest that equal loudness filtering and frequency/amplitude correction methods provide significant improvements, whilst using a multi-resolution spectral transform results in only a marginal improvement compared to the standard STFT. The effect of key parameters in the computation of the salience function is also studied and discussed.
Download Soundscape auralisation and visualisation: A cross-modal approach to Soundscape evaluation Soundscape research is concerned with the study and understanding of our relationship with our surrounding acoustic environments and the sonic elements that they are comprised of. Whilst much of this research has focussed on sound alone, any practical application of soundscape methodologies should consider the interaction between aural and visual environmental features: an interaction known as cross-modal perception. This presents an avenue for soundscape research exploring how an environment’s visual features can affect an individual’s experience of the soundscape of that same environment. This paper presents the results of two listening tests1 : one a preliminary test making use of static stereo UHJ renderings of first-order-ambisonic (FOA) soundscape recordings and static panoramic images; the other using YouTube as a platform to present dynamic binaural renderings of the same FOA recordings alongside full motion spherical video. The stimuli for these tests were recorded at several locations around the north of England including rural, urban, and suburban environments exhibiting soundscapes comprised of many natural, human, and mechanical sounds. The purpose of these tests was to investigate how the presence of visual stimuli can alter soundscape perception and categorisation. This was done by presenting test subjects with each soundscape alone and then with visual accompaniment, and then comparing collected subjective evaluation data. Results indicate that the presence of certain visual features can alter the emotional state evoked by exposure to a soundscape, for example, where the presence of ‘green infrastructure’ (parks, trees, and foliage) results in a less agitating experience of a soundscape containing high levels of environmental noise. This research represents an important initial step toward the integration of virtual reality technologies into soundscape research, and the use of suitable tools to perform subjective evaluation of audiovisual stimuli. Future research will consider how these methodologies can be implemented in real-world applications.
Download Audio Time-Scaling for Slow Motion Sports Videos Slow motion videos are frequently featured during broadcast of sports events. However, these videos do not feature any audio channel, apart from the live ambiance and comments from sports presenters. Standard audio time-scaling methods were not developed with such noisy signal in mind and they do not always permit to obtain an acceptable acoustic quality. In this work, we present a new approach that creates high-quality time-stretched version of sport audio recordings while preserving all their transient events.
Download Voice Features For Control: A Vocalist Dependent Method For Noise Measurement And Independent Signals Computation Information about the human spoken and singing voice is conveyed through the articulations of the individual’s vocal folds and vocal tract. The signal receiver, either human or machine, works at different levels of abstraction to extract and interpret only the relevant context specific information needed. Traditionally in the field of human machine interaction, the human voice is used to drive and control events that are discrete in terms of time and value. We propose to use the voice as a source of realvalued and time-continuous control signals that can be employed to interact with any multidimensional human-controllable device in real-time. The isolation of noise sources and the independence of the control dimensions play a central role. Their dependency on individual voice represents an additional challenge. In this paper we introduce a method to compute case specific independent signals from the vocal sound, together with an individual study of features computation and selection for noise rejection.