Abstract: Neural vocoders, used for converting the spectral representations of an audio signal to the waveforms, are a commonly used component in speech synthesis pipelines. It focuses on synthesizing ...

I just rewrote the WaveGlow vocoder in tensorflow trying to improve its performance but it fails (1.7 sec generated / sec with the pytorch model drops down to less than 1.2 generated / sec in ...

Abstract: This article presents a neural vocoder named HiNet which reconstructs speech waveforms from acoustic features by predicting amplitude and phase spectra hierarchically. Different from ...

Recent advancements in speech synthesis have leveraged GAN-based networks like HiFi-GAN and BigVGAN to produce high-fidelity waveforms from mel-spectrograms. However, these networks are ...

This is achieved through the use of the latest state-of-the-art voice coding technology called Tri-Wave Excited Linear Prediction, developed by the digital voice coding experts at DSP Innovations.

Ask the publishers to restore access to 500,000+ books. An icon used to represent a menu that can be toggled by interacting with this icon. A line drawing of the Internet Archive headquarters building ...

Many new implementations of vocoder algorithms are designed to provide higher-quality voice at lower data rates. However, the sensitivity and transmitter quality of a mobile handset affects vocoder ...

1-24 — elektor january 1980 elektor vocoder (1) an absolute first! After all the articles describing the theory of vocoders, there must be a lot of enthusiastic readers just itching to build one.