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Gupta et al., 2023 - Google Patents

Towards controllable audio texture morphing

Gupta et al., 2023

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Document ID
10945618946294180945
Author
Gupta C
Kamath P
Wei Y
Li Z
Nanayakkara S
Wyse L
Publication year
Publication venue
ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

External Links

Snippet

In this paper, we propose a data-driven approach to train a Generative Adversarial Network (GAN) conditioned on" soft-labels" distilled from the penultimate layer of an audio classifier trained on a target set of audio texture classes. We demonstrate that interpolation between …
Continue reading at arxiv.org (PDF) (other versions)

Classifications

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    • G10L25/90Pitch determination of speech signals
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    • G10MUSICAL INSTRUMENTS; ACOUSTICS
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    • G10H2210/00Aspects or methods of musical processing having intrinsic musical character, i.e. involving musical theory or musical parameters or relying on musical knowledge, as applied in electrophonic musical tools or instruments
    • G10H2210/031Musical analysis, i.e. isolation, extraction or identification of musical elements or musical parameters from a raw acoustic signal or from an encoded audio signal
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    • G10L25/48Speech or voice analysis techniques not restricted to a single one of groups G10L15/00-G10L21/00 specially adapted for particular use
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    • G10L19/00Speech or audio signal analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signal, using source filter models or psychoacoustic analysis
    • G10L19/02Speech or audio signal analysis-synthesis techniques for redundancy reduction, e.g. in vocoders; Coding or decoding of speech or audio signal, using source filter models or psychoacoustic analysis using spectral analysis, e.g. transform vocoders or subband vocoders
    • GPHYSICS
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