Data annotation project involving the segmentation and transcription of a 10-hour recorded sermons using Loft 2.0. I worked with audio data by identifying speech segments, assigning speaker labels, and producing accurate transcriptions aligned with the relevant audio segments. The work required careful listening, precise time segmentation, consistent labeling, and attention to transcription quality.

The screenshot shows a 6-minute sample from the larger 10 -hour audio annotation project. Full source material is not publicly shared. 

I am currently working on a video annotation project using CVAT, labeling vehicles such as cars and trucks with bounding boxes across video frames. The project focuses on creating accurate and consistent visual data for AI model training and computer vision applications, with particular attention to object identification, classification, and annotation quality