Encoder Factorization for Capturing Dialect and Articulation Level in End-to-End Speech Synthesis

期間：2019年9月 – 2021年3月
助成種目：日本学術振興会 科学研究費助成事業 研究活動スタート支援
課題番号：19K24372
URL：https://kaken.nii.ac.jp/ja/grant/KAKENHI-PROJECT-19K24372/

Synthesizing speech in a variety of speaker voices and styles has long been a goal in speech research. Recent advances in speech synthesis have resulted in very natural-sounding synthetic speech. Current approaches to modeling multiple speakers in synthetic speech have resulted in high similarity to the different speakers, but fail to capture characteristics such as dialect and level of articulation. We aim to determine whether including models of dialect and level of articulation in synthetic speech systems can successfully capture these aspects of speech.