Worked on the music-assistant/server repository to deliver album loudness normalization and presentation, focusing on enhancing the listening experience by reducing volume disparities between tracks within an album. Implemented backend logic in Python to prioritize album-level loudness during playback, ensuring accurate detection of albums in playback queues by analyzing track context. Improved data formatting by rounding loudness measurements for consistent frontend display, aligning backend audio processing with user interface requirements. The work leveraged skills in audio processing, backend development, and music playback logic, resulting in more reliable loudness data and smoother transitions for users listening to albums through the platform.