CONF Chen_BLIZZARD2023_2023/IDIAP The Idiap Speech Synthesis System for the Blizzard Challenge 2023 Chen, Haolin He, Mutian Coppieters de Gibson, Louise Garner, Philip N. Blizzard Challenge diffusion transformer French TTS speech synthesis EXTERNAL http://publications.idiap.ch/attachments/papers/2023/Chen_BLIZZARD2023_2023.pdf PUBLIC Proc. 18th Blizzard Challenge Workshop 2023 10.21437/Blizzard.2023-13 doi This paper presents the text-to-speech (TTS) system submitted by Idiap Research Institute to the Blizzard Challenge 2023. Our system follows the conventional pipeline of text analysis, acoustic modeling (AM) and vocoding. For text analysis, open-source pretrained part-of-speech (POS) taggers and lemmatizers are utilized to provide more accurate grapheme-to-phoneme (G2P) conversion on top of the eSpeak backend. The rest of the system incorporates a fully diffusion-based approach which comprises a diffusion transformer-based acoustic model and FastDiff as the vocoder, both of which are trained only on the provided data to ensure high-quality synthesis. Our entry provides a baseline for the cascading diffusion AM-vocoder architecture since no extra design is adopted to enhance the naturalness of speech. Evaluation results have demonstrated high synthesis quality of our system and the effectiveness of the proposed phonemization pipeline.