Worked on improving the stability of the resemble-ai/chatterbox speech processing pipeline by addressing a recurring CUDA error. Introduced a threshold-based filter for speech token values, ensuring they remained within safe operational limits and thereby reducing the likelihood of CUDA-related runtime failures. This solution enhanced the reliability and uptime of the audio processing system, directly benefiting production environments. The work involved applying expertise in Python, CUDA, and machine learning to identify the root cause and implement a targeted fix. All changes were clearly documented and linked to the relevant issue, improving traceability and maintainability for future development and troubleshooting efforts.