VocBench: A Neural Vocoder Benchmark for Speech Synthesis

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 waveforms from low-dimensional representation, such as Mel-Spectrograms. In recent years, different approaches have been introduced to develop such vocoders. However, it becomes more challenging to assess these new vocoders and compare their performance to previous ones. To address this problem, we present VocBench, a framework that benchmark the performance of state-of-the art neural vocoders. 2021: Ehab A. AlBadawy, Andrew Gibiansky, Qing He, Jilong Wu, Ming-Ching Chang, Siwei Lyu https://arxiv.org/pdf/2112.03099v1.pdf