A dataset of audio clips was prepared and audio quality assessed by subjective testing. Encoded as digital signals, a large amount of feature-extraction was possible. A new objective metric is proposed, describing the Gaussian nature of a signal’s amplitude distribution. Correlations between objective measurements of the music signals and the subjective perception of their quality were found. Existing metrics were adjusted to match quality perception. A number of timbral, spatial, rhythmic and amplitude measures, in addition to predictions of emotional response, were found to be related to the perception of quality. The emotional features were found to have most importance, indicating a connection between quality and a unified set of subjective and objective parameters.

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Since digital audio is encoded as discrete samples of the audio waveform, much can be said about a recording by the statistical properties of these samples. In this paper, a dataset of CD audio samples is analysed; the probability mass function of each audio clip informs a feature set which describes attributes of the musical recording related to loudness, dynamics and distortion. This allows musical recordings to be classified according to their “distortion character”, a concept which describes the nature of amplitude distortion in mastered audio. A subjective test was designed in which such recordings were rated according to the perception of their audio quality. It is shown that participants can discern between three different distortion characters; ratings of audio quality were significantly different (F (1, 2) = 5.72, p < 0.001, η 2 = 0.008) as were the words used to describe the attributes on which quality was assessed (χ2 (8, N = 547) = 33.28, p < 0.001). This expands upon previous work showing links between the effects of dynamic range compression and audio quality in musical recordings, by highlighting perceptual differences.

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This paper presents the co-authorship network of the DAFx conference series, from its inception in 1998 to the present, along with subsequent analysis. In total 1,281 unique authors have contributed 1,175 unique submissions to this conference series. The co-authorship network is revealed to contain a large weakly connected component containing 667 authors (≈52% of the total network). The size of this component compares well to previous studies of other conference series of similar age and scope. Within this connected component, 24 communities were detected using the Louvain method. While some communities have formed based on geographic proximity, links between communities are observed. This shows a high level of collaboration in the network, possibly due to the speciality of the conference and the movement of academics throughout Europe.

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