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arXiv · 2308.02418

Differentiable adaptive short-time Fourier transform with respect to the window length

Maxime Leiber·Yosra Marnissi·Axel Barrau·Mohammed El Badaoui
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Abstract

This paper presents a gradient-based method for on-the-fly optimization for both per-frame and per-frequency window length of the short-time Fourier transform (STFT), related to previous work in which we developed a differentiable version of STFT by making the window length a continuous parameter. The resulting differentiable adaptive STFT possesses commendable properties, such as the ability to adapt in the same time-frequency representation to both transient and stationary components, while being easily optimized by gradient descent. We validate the performance of our method in vibration analysis.

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Maxime Leiber, Yosra Marnissi, Axel Barrau, Mohammed El Badaoui. 2023-07-26. Differentiable adaptive short-time Fourier transform with respect to the window length. https://doi.org/10.1109/icassp49357.2023.10095245

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