Video Annotator Reviewer
o Reviewed and created comprehensive descriptions for thousands of AI generated videos by quickly providing ratings for visual and audible problems and tagged hundreds of audio clips with emotion tags.
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I am a detail-oriented professional with extensive experience in data labeling, annotation, and AI training across diverse domains including computer vision, NLP, and audio processing. My background includes reviewing and annotating thousands of AI-generated videos, images, and audio clips, as well as enhancing AI model performance by rating, tagging, and providing high-quality audio recordings for TTS scripts. I am skilled in prompt engineering, data analysis, and content optimization, with hands-on expertise using platforms like Labelbox and Pega CRM. My strong technical abilities, fast learning, and commitment to data integrity ensure accurate, efficient, and high-quality training data for AI systems. I thrive in remote environments and am passionate about leveraging generative AI to improve operational efficiency and data quality.
o Reviewed and created comprehensive descriptions for thousands of AI generated videos by quickly providing ratings for visual and audible problems and tagged hundreds of audio clips with emotion tags.
Recorded hundreds of audio clips for simple and complex professional prompts, with meticulous accuracy, varying pitches, and avid expressions.
This is a project to determine the efficiency and accuracy of AI generated videos involving 500+ people for 2,000 to 4,000 annotations each day.
o Provided studio quality recordings for voice acting, emotional expression, and narrative audio, editing to perfection and providing accurate timing synchronization at 44.1 kHz, 24-bit format for an AI training project.
This was a 6 week project to create human and AI prompts and responses involving 500+ people for evaluation and rating to determine the quality, clarity, and efficiency of data to teach AI.
High School Diploma, General Studies
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