Paper ID: 2501.01650 • Published Jan 3, 2025
An efficient light-weighted signal reconstruction method consists of Fast Fourier Transform and Convolutional-based Autoencoder
Pu-Yun Kow, Pu-Zhao Kow
TL;DR
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The main theme of this paper is to reconstruct audio signal from interrupted
measurements. We present a light-weighted model only consisting discrete
Fourier transform and Convolutional-based Autoencoder model (ConvAE), called
the FFT-ConvAE model for the Helsinki Speech Challenge 2024. The FFT-ConvAE
model is light-weighted (in terms of real-time factor) and efficient (in terms
of character error rate), which was verified by the organizers. Furthermore,
the FFT-ConvAE is a general-purpose model capable of handling all tasks with a
unified configuration.