Digital effects are most of the time non-adaptive: they are applied with the same control values during the whole sound. Adaptive digital audio effects are controlled by features extracted from the sound itself. This means that both a time-frequency features extraction and a mapping from these features to effects parameters are needed. This way, the usual DAFx class is extended to a wider class, the adaptive DAFx one. Four A-DAFx are proposed in this paper, based on the phase vocoder technique: a selective timestretching, an adaptive granular delay, an adaptive robotization and an adaptive whisperization. They provide interesting sounds for electroacoustic and electronic music, with a great coherence between the effect and the original sound.

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Adaptive digital audio effects require several implementations, according to the context. This paper brings out a general adaptive DAFx diagram, using one or two input sounds and gesture control of the mapping. Effects are classified according to the perceptive parameters that the effects modify. New adaptive effects are presented, such as martianization and vowel colorization. Some items are highlighted, such as specific problems of real-time and non real-time implementation, improvements with control curve scaling, and solutions to particular problems, like quantization methods for delay-line based effects. To illustrate, musical applications are pointed out.

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This article intends to demonstrate how a specific digital audio effect can benefit from a proper control, be it from sounds and/or from gesture. When this control is from sounds, it can be called “adaptive” or “sound automated”. When this control is from gesture, it can be called “gesturally controlled”. The audio effects we use for this demonstration are time-scaling and pitch-shifting in the particular contexts of vibrato, prosody change, time unfolding and rythm change.

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This paper takes the opportunity of presenting a set of new adaptive effects to propose a generic scheme for adaptive effects built upon a spectral source-filter decomposition and a Short-Time Fourier analysis-resynthesis. This allows for a better formalization of the involved signal processing algorithms and leads to a simple classification of adaptive effects already presented in the literature, that falls into this category. We discuss the motivation and the advantages of combining source-filter modeling and phase vocoder representation for the design of adaptive digital audio effects. Then we detail the general structure that includes STFT analysis and re-synthesis scheme, the source filter decomposition, and an adaptive control unit composed of a feature extraction system and a sound mapping unit that might be driven by a gestural control section.

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The aim of this paper is to propose an interdisciplinary classification of digital audio effects to facilitate communication and collaborations between DSP programmers, sound engineers, composers, performers and musicologists. After reviewing classifications reflecting technological, technical and perceptual points of view, we introduce a transverse classification to link disciplinespecific classifications into a single network containing various layers of descriptors, ranging from low-level features to high-level features. Simple tools using the interdisciplinary classification are introduced to facilitate the navigation between effects, underlying techniques, perceptual attributes and semantic descriptors. Finally, concluding remarks on implications for teaching purposes and for the development of audio effects user interfaces based on perceptual features rather than technical parameters are presented.

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