Phrase break prediction with bidirectional encoder representations in Japanese text-to-speech synthesis Kosuke Futamata, Byeongseon Park, Ryuichi Yamamoto, Kentaro Tachibana Apr 2, 2021 Go to Project Site Deep Learning NLP Interspeech 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 A Unified Accent Estimation Method Based on Multi-Task Learning for Japanese Text-to-Speech DRSpeech: Degradation-Robust Text-to-Speech Synthesis with Frame-Level and Utterance-Level Acoustic Representation Learning TTS-by-TTS 2: Data-selective Augmentation for Neural Speech Synthesis Using Ranking Support Vector Machine with Variational Autoencoder Cross-Speaker Emotion Transfer for Low-Resource Text-to-Speech Using Non-Parallel Voice Conversion with Pitch-Shift Data Augmentation Language Model-Based Emotion Prediction Methods for Emotional Speech Synthesis Systems