Jiamei Rong developed a custom Text Normalization (TN) training capability for the Azure-Samples/cognitive-services-speech-sdk repository, focusing on enhancing model customization for domain-specific vocabularies. Using C++ and the Speech SDK, Jiamei expanded multi-letter unit (mN) handling and refined single-letter unit rules to improve training data precision and reduce noise, directly impacting end-user model performance. The work involved implementing explicit TN workflows and aligning code changes with project roadmap goals, emphasizing feature delivery and code quality. Although no major bugs were addressed during this period, Jiamei’s contributions demonstrated depth in C++ development and a targeted approach to speech model improvement.