Bandwidth In Dsp
%20increasing%20the%20effective%20sampling%20rate%20of%20speech%20signals%20from%208%20kHz%20to%2048%20kHz.%20Unlike%20existing%20end-to-end%20deep%20learning%20models%2C%20our%20proposed%20method%20explicitly%20models%20BWE%20using%20excitation%20and%20linear%20time-varying%20(LTV)%20filter%20stages.%20The%20excitation%20stage%20broadens%20the%20spectrum%20of%20the%20input%2C%20while%20the%20filtering%20stage%20properly%20shapes%20it%20based%20on%20outputs%20from%20an%20acoustic%20feature%20predictor.%20To%20this%20end%2C%20an%20acoustic%20feature%20loss%20term%20can%20implicitly%20promote%20the%20excitation%20subnetwork%20to%20produce%20white%20spectra%20in%20the%20upper%20frequency%20band%20to%20be%20synthesized.%20Experimental%20results%20demonstrate%20that%20the%20added%20inductive%20bias%20provided%20by%20our%20approach%20can%20improve%20upon%20BWE%20results%20using%20the%20generators%20from%20both%20SEANet%20or%20HiFi-GAN%20as%20exciters%2C%20and%20that%20our%20means%20of%20adapting%20processing%20with%20acoustic%20feature%20predictions%20is%20more%20effective%20than%20that%20used%20in%20HiFi-GAN-2.%20Secondary%20contributions%20include%20extensions%20of%20the%20SEANet%20model%20to%20accommodate%20local%20conditioning%20information%2C%20as%20well%20as%20the%20application%20of%20HiFi-GAN-2%20for%20the%20BWE%20problem.)
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![[DIAGRAM] Diagram Of Signal - MYDIAGRAM.ONLINE](https://i.ytimg.com/vi/xAc4TSp87IY/maxresdefault.jpg)
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