1,809 research outputs found

    Real-time Timbre Remapping with Differentiable DSP

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    Timbre is a primary mode of expression in diverse musical contexts. However, prevalent audio-driven synthesis methods predominantly rely on pitch and loudness envelopes, effectively flattening timbral expression from the input. Our approach draws on the concept of timbre analogies and investigates how timbral expression from an input signal can be mapped onto controls for a synthesizer. Leveraging differentiable digital signal processing, our method facilitates direct optimization of synthesizer parameters through a novel feature difference loss. This loss function, designed to learn relative timbral differences between musical events, prioritizes the subtleties of graded timbre modulations within phrases, allowing for meaningful translations in a timbre space. Using snare drum performances as a case study, where timbral expression is central, we demonstrate real-time timbre remapping from acoustic snare drums to a differentiable synthesizer modeled after the Roland TR-808

    Real-time Timbre Transfer and Sound Synthesis using DDSP

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    Neural audio synthesis is an actively researched topic, having yielded a wide range of techniques that leverages machine learning architectures. Google Magenta elaborated a novel approach called Differential Digital Signal Processing (DDSP) that incorporates deep neural networks with preconditioned digital signal processing techniques, reaching state-of-the-art results especially in timbre transfer applications. However, most of these techniques, including the DDSP, are generally not applicable in real-time constraints, making them ineligible in a musical workflow. In this paper, we present a real-time implementation of the DDSP library embedded in a virtual synthesizer as a plug-in that can be used in a Digital Audio Workstation. We focused on timbre transfer from learned representations of real instruments to arbitrary sound inputs as well as controlling these models by MIDI. Furthermore, we developed a GUI for intuitive high-level controls which can be used for post-processing and manipulating the parameters estimated by the neural network. We have conducted a user experience test with seven participants online. The results indicated that our users found the interface appealing, easy to understand, and worth exploring further. At the same time, we have identified issues in the timbre transfer quality, in some components we did not implement, and in installation and distribution of our plugin. The next iteration of our design will address these issues. Our real-time MATLAB and JUCE implementations are available at https://github.com/SMC704/juce-ddsp and https://github.com/SMC704/matlab-ddsp , respectively

    PnP Maxtools: Autonomous Parameter Control in MaxMSP Utilizing MIR Algorithms

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    This research presents a new approach to computer automation through the implementation of novel real-time music information retrieval algorithms developed for this project. It documents the development of the PnP.Maxtools package, a set of open source objects designed within the popular programming environment MaxMSP. The package is a set of pre/post processing filters, objective and subjective timbral descriptors, audio effects, and other objects that are designed to be used together to compose music or improvise without the use of external controllers or hardware. The PnP.Maxtools package objects are designed to be used quickly and easily using a `plug and play\u27 style with as few initial arguments needed as possible. The PnP.Maxtools package is designed to take incoming audio from a microphone, analyze it, and use the analysis to control an audio effect on the incoming signal in real-time. In this way, the audio content has a real musical and analogous relationship with the resulting musical transformations while the control parameters become more multifaceted and better able to serve the needs of artists. The term Reflexive Automation is presented that describes this unsupervised relationship between the content of the sound being analyzed and the analogous and automatic control over a specific musical parameter. A set of compositions are also presented that demonstrate ideal usage of the object categories for creating reflexive systems and achieving fully autonomous control over musical parameters

    Comparison of input devices in an ISEE direct timbre manipulation task

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    The representation and manipulation of sound within multimedia systems is an important and currently under-researched area. The paper gives an overview of the authors' work on the direct manipulation of audio information, and describes a solution based upon the navigation of four-dimensional scaled timbre spaces. Three hardware input devices were experimentally evaluated for use in a timbre space navigation task: the Apple Standard Mouse, Gravis Advanced Mousestick II joystick (absolute and relative) and the Nintendo Power Glove. Results show that the usability of these devices significantly affected the efficacy of the system, and that conventional low-cost, low-dimensional devices provided better performance than the low-cost, multidimensional dataglove

    Concatenative Synthesis for Novel Timbral Creation

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    Modern day musicians rely on a variety of instruments for musical expression. Tones produced from electronic instruments have become almost as commonplace as those produced by traditional ones as evidenced by the plethora of artists who can be found composing and performing with nothing more than a personal computer. This desire to embrace technical innovation as a means to augment performance art has created a budding field in computer science that explores the creation and manipulation of sound for artistic purposes. One facet of this new frontier concerns timbral creation, or the development of new sounds with unique characteristics that can be wielded by the musician as a virtual instrument. This thesis presents Timcat, a software system that can be used to create novel timbres from prerecorded audio. Various techniques for timbral feature extraction from short audio clips, or grains, are evaluated for use in timbral feature spaces. Clustering is performed on feature vectors in these spaces and groupings are recombined using concatenative synthesis techniques in order to form new instrument patches. The results reveal that interesting timbres can be created using features extracted by both newly developed and existing signal analysis techniques, many common in other fields though not often applied to music audio signals. Several of the features employed also show high accuracy for instrument separation in randomly mixed tracks. Survey results demonstrate positive feedback concerning the timbres created by Timcat from electronic music composers, musicians, and music lovers alike

    A toolkit for interactive sonification

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    Presented at the 10th International Conference on Auditory Display (ICAD2004)This paper describes work-in-progress on an Interactive Sonification Toolkit which has been developed in order to aid the analysis of general data sets. The toolkit allows the designer to process and scale data sets, then rapidly change the sonification method. The human user can then interact with the data in a fluid manner, continually controlling the position within the set. The interface used by default is the computer mouse, but we also describe plans for multiparametric interfaces which will allow real-time control of many aspects of the data. Early results of interactive sonic analysis of two example domains are described, but extensive user tests are being planned
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