Period VITS: Variational Inference With Explicit Pitch Modeling For End-to-End Emotional Speech Synthesis Yuma Shirahata, Ryuichi Yamamoto, Eunwoo Song, Ryo Terashima, Jae-Min Kim, Kentaro Tachibana Oct 18, 2022 Go to Project Site Deep Learning End-to-End TTS ICASSP Ryuichi Yamamoto Engineer/Researcher I am a engineer/researcher passionate about speech synthesis. I love to write code and enjoy open-source collaboration on GitHub. Please feel free to reach out on Twitter and GitHub. Related ESPnet2-TTS: Extending the Edge of TTS Research TTS-by-TTS: TTS-driven Data Augmentation for Fast and High-Quality Speech Synthesis Parallel waveform synthesis based on generative adversarial networks with voicing-aware conditional discriminators ESPnet-TTS: Unified, Reproducible, and Integratable Open Source End-to-End Text-to-Speech Toolkit Parallel WaveGAN: A fast waveform generation model based on generative adversarial networks with multi-resolution spectrogram