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Deep Dive: Unsupervised Audio Processing with Differentiable Digital Signal Processing (DDSP)
Traditional audio processing often relies on labeled data, hindering its scalability and efficiency. This session delves into Differentiable Digital Signal Processing (DDSP), a revolutionary approach that enables unsupervised learning for various audio tasks. We'll explore the core principles of DDSP and its advantages for audio processing.
The presentation will showcase how DDSP can be harnessed for tasks like feature extraction, audio parameterization, and even audio generation – all without the need for extensive labeled datasets. Crucially, DDSP allows us to learn the inherent structural priors of audio data itself. This refers to the underlying patterns and relationships within audio signals that DDSP can leverage to perform complex tasks without explicit human guidance.
Through real-world examples and case studies, we'll gain insights into how DDSP is pushing the boundaries of unsupervised audio processing.