Paper Archive

In this paper, we propose a parametric audio coding framework that combines the analysis and re-synthesis of electric bass guitar recordings. In particular, an existing synthesis algorithm that incorporates 11 playing techniques is extended by two calibration algorithms. Both the temporal and spectral decay parameters as well as the inharmonicity coefficient are set according to the fretboard position on the instrument. Listening tests show that there is still a gap in perceptual quality between real-world instrument recordings and the re-synthesized versions. Due to this gap, the perceived improvement due to the model calibration is only small. Second, the listening tests reveal that the plucking styles are more important towards realistic synthesis results than expression styles.

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We revisit pulsetable synthesis, an efficient technique for generating plausible and expressive wind instrument tones. Based on the principles of pulse forming theory, this method models sound production as the periodic repetition of shaped pulses characterizing the target instruments' spectral envelope. In this approach, single-cycle waveforms, referred to as pulses, are stored in pulsetables indexed by their corresponding fundamental frequency. During synthesis, the pulses are read from these tables to form a periodic waveform, which is further shaped by time-varying low-pass filtering, amplification, and reverberation. These processes are guided by control signal contours that describe how fundamental frequency, brightness, and loudness evolve over time. Through case studies with real-world wind instrument recordings, we show how the interplay between these control signals gives rise to articulations such as attack transients, vibrato, and growl. Finally, we discuss the potential of this framework for integration into Differentiable Digital Signal Processing (DDSP) models, where neural networks could learn synthesis parameters directly from training data.

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In this paper we present a novel algorithm for automatic analysis, transcription, and parameter extraction from isolated polyphonic guitar recordings. In addition to general score-related information such as note onset, duration, and pitch, instrumentspecific information such as the plucked string, the applied plucking and expression styles are retrieved automatically. For this purpose, we adapted several state-of-the-art approaches for onset and offset detection, multipitch estimation, string estimation, feature extraction, and multi-class classification. Furthermore we investigated a robust partial tracking algorithm with respect to inharmonicity, an extensive extraction of novel and known audio features as well as the exploitation of instrument-based knowledge in the form of plausability filtering to obtain more reliable prediction. Our system achieved very high accuracy values of 98 % for onset and offset detection as well as multipitch estimation. For the instrument-related parameters, the proposed algorithm also showed very good performance with accuracy values of 82 % for the string number, 93 % for the plucking style, and 83 % for the expression style. Index Terms - playing techniques, plucking style, expression style, multiple fundamental frequency estimation, string classification, fretboard position, fingering, electric guitar, inharmonicity coefficient, tablature

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Separation of instrument sounds from polyphonic music recordings is a desirable signal processing function with a wide variety of applications in music production, video games and information retrieval. In general, sound source separation algorithms attempt to exploit those characteristics of audio signals that differentiate one from the other. Many algorithms have studied spectral magnitude as a means for separation tasks. Here we propose the exploration of phase information of musical instrument signals as an alternative dimension in discriminating sound signals originating from different sources. Three cases are presented: (1) Phase contours of musical instruments notes as potential separation features. (2) Resolving overlapping harmonics using phase coupling properties of musical instruments. (3) Harmonic percussive decomposition using calculated radian ranges for each frequency bin.

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