This paper describes the La Forge entry to the Blizzard Challenge of 2023 focusing on text-to-speech in French and homograph disambiguation. Our system is based on VAE-Tacotron and HiFi-GAN. We implement several improvements on the baseline models such as a cycle consistency loss for better style modeling, a style reference selection method to improve overall naturalness and an over-produce and select method that chooses the best synthesized candidate across multiple variations using automatic speech recognition. We also build a linguistic frontend capable of homograph disambiguation using part-of-speech tagging and simple rules. We publicly release our hand annotated data set for French homograph disambiguation. Results from subjective listening tests show the effectiveness of our system in disambiguating homographs and generating high-quality synthetic speech.