catherine qin

Performed image data cleansing and semantic segmentation using X-Anylabeling tool for deep learning applications. Ensured high-quality image annotation based on specific application scenarios.

Conducted quality reviews for generative music across various styles. Applied linguistic and musical knowledge to enhance AI/ML data quality for music datasets.

Conducted semantic similarity and audio quality MOS evaluations. Worked with clients like Google and Tencent, ensuring high standards in data annotation.

Assessed Chinese-English machine translation outputs and evaluated AI response quality. Specialized in Machine Translation and Model QA Evaluation for multilingual datasets.

Performed English OCR annotation, German game labeling, and generative video evaluation. Promoted to Quality Inspector due to consistent high performance.

Processed speech and game audio, performed multilingual labeling (EN/CN), and developed AI training data. Supported clients with high-quality data for AI/ML projects.

Studied English Language and Literature, focusing on translation, interpretation, German literature, linguistics, rhetoric, and cross-cultural studies. Completed a thesis on multilingual translation quality assessment of CPC historical documents.

Gained basic knowledge of big data and business administration. This program provided foundational computer science skills relevant to AI/ML data quality.