This study examines the potential of visual feedback to improve Mandarin tone acquisition among second language learners. It focuses on a custom-built mobile application designed to provide real-time feedback on pronunciation through pitch contour analysis. At the time of writing, the app includes a foundational module that introduces all four Chinese tones and enables users to visualize their pronunciation performance. Unlike popular language-learning platforms such as Duolingo or Rosetta Stone, which do not provide real-time pitch contour analysis or vowel feedback for tonal languages, this app fills a critical gap in existing tools by offering a novel approach to feedback. The study evaluates the effectiveness of visual feedback through A/B testing. Both experimental and control groups will use the app; however, the experimental group will receive both visual and textual feedback, while the control group will interact only with textual feedback. The key metric for evaluation include pronunciation accuracy, and I hypothesize that learners who use visual feedback will achieve better accuracy than learners who only have textual feedback. The app development will be completed in Fall 2024, and the study will be carried out in Spring 2025. By integrating linguistic theory with technology, this research contributes to the field of second language acquisition by incorporating advanced visual feedback mechanisms into the learning process. Additionally, it seeks to understand how interactive, feedback-driven approaches can address persistent challenges in learning tonal languages like Mandarin.