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Comparison of discrete transforms for deep‐neural‐networks‐based speech enhancement
Abstract In recent studies of speech enhancement, a deep‐learning model is trained to predict clean speech spectra from the known noisy spectra of speech. Rather than using the traditional discrete Fourier transform (DFT), this paper considers other well‐known transforms to generate the speech spect...
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| Autori principali: | , |
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| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Wiley
2022-06-01
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| Serie: | IET Signal Processing |
| Soggetti: | |
| Accesso online: | https://doi.org/10.1049/sil2.12109 |
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