The paper focuses on inpainting missing parts of an audio signal spectrogram. The autoregression-based Janssen algorithm, the state-of-the-art for the time-domain audio inpainting, is adapted for the time-frequency setting. This novel method, termed Janssen-TF, is compared to the deep-prior neural network approach using both objective metrics and a~subjective listening test, proving Janssen-TF to be superior in all the considered measures.
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