Go witheFlow: Real-time Emotion Driven Audio Effects Modulation
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Abstract (arXiv)
Music performance is a distinctly human activity, intrinsically linked to the performer's ability to convey, evoke, or express emotion. Machines cannot perform music in the human sense; they can produce, reproduce, execute, or synthesize music, but they lack the capacity for affective or emotional experience. As such, music performance is an ideal candidate through which to explore aspects of collaboration between humans and machines. In this paper, we introduce the witheFlow system, designed to enhance real-time music performance by automatically modulating audio effects based on features extracted from both biosignals and the audio itself. The system, currently in a proof-of-concept phase, is designed to be lightweight, able to run locally on a laptop, and is open-source given the availability of a compatible Digital Audio Workstation and sensors.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 7 of its 22 references that are in the map. First posted on arXiv 2 Oct 2025.
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7 of 22 references.
References · 7
- 2019PANNs: Large-Scale Pretrained Audio Neural Networks for Audio Pattern Recognitioncited by 563
- 2020DDSP: Differentiable Digital Signal Processingcited by 177
- 2021MIDI-DDSP: Detailed Control of Musical Performance via Hierarchical Modelingcited by 31
- 2019Autonomy, Authenticity, Authorship and Intention in computer generated artcited by 18
- 2023Symbolic Music Representations for Classification Tasks: A Systematic Evaluationcited by 14
- 2023A Survey of AI Music Generation Tools and Modelscited by 9
- 2025Music Interpretation and Emotion Perception: A Computational and Neurophysiological Investigationcited by 2
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