9 citations · 16 across the 12 of their papers we have counts for
3 papers · 1 filter
Learning Disentangled Phone and Speaker Representations in a Semi-Supervised VQ-VAE Paradigm
Jennifer Williams, Yi Zhao, Erica Cooper +1
We present a new approach to disentangle speaker voice and phone content by introducing new components to the VQ-VAE architecture for speech synthesis. The original VQ-VAE does not…
Improved Prosody from Learned F0 Codebook Representations for VQ-VAE Speech Waveform Reconstruction
Yi Zhao, Haoyu Li, Cheng-I Lai +3
Vector Quantized Variational AutoEncoders (VQ-VAE) are a powerful representation learning framework that can discover discrete groups of features from a speech signal without super…
Comparison of Speech Representations for Automatic Quality Estimation in Multi-Speaker Text-to-Speech Synthesis
Jennifer Williams, Joanna Rownicka, Pilar Oplustil +1
We aim to characterize how different speakers contribute to the perceived output quality of multi-speaker Text-to-Speech (TTS) synthesis. We automatically rate the quality of TTS u…