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: 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 ...

Abstract: Recently, BigVGAN has emerged as high-performance speech vocoder. Its sequence-to-sequence-based synthesis, however, prohibits usage in low-latency conversational applications. Our work ...

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 ...

The development of neural networks and their constantly increasing popularity have led to substantial improvements in speech synthesis technologies. The majority of speech synthesis systems use a ...

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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.

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.