AERO: Audio Super Resolution in the Spectral Domain

We present AERO, a audio super-resolution model that processes speech and music signals in the spectral domain. AERO is based on an encoder-decoder architecture with UNet like skip connections. We optimize the model using both time and frequency domain loss functions. Specifically, we consider a set...

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Bibliographic Details
Main Authors: Mandel, Moshe, Tal, Or, Adi, Yossi
Format: Conference Proceeding
Language:English
Subjects:
audio super-resolution
Bandwidth
bandwidth extension
Codes
Frequency-domain analysis
High frequency
Multiple signal classification
Speech processing
speech synthesis
Superresolution
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Description
Summary:We present AERO, a audio super-resolution model that processes speech and music signals in the spectral domain. AERO is based on an encoder-decoder architecture with UNet like skip connections. We optimize the model using both time and frequency domain loss functions. Specifically, we consider a set of reconstruction losses together with perceptual ones in the form of adversarial and feature discriminator loss functions. To better handle phase information the proposed method operates over the complex-valued spectrogram using two separate channels. Unlike prior work which mainly considers low and high frequency concatenation for audio super-resolution, the proposed method directly predicts the full frequency range. We demonstrate high performance across a wide range of sample rates considering both speech and music. AERO outperforms the evaluated baselines considering Log-Spectral Distance, ViSQOL, and the subjective MUSHRA test. Audio samples and code are available {\color{Blue}\text{here}}.
ISSN:2379-190X
DOI:10.1109/ICASSP49357.2023.10095382