speech labelling
converting audio to text, labelling who is speaking, tagging sounds and sounds.
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I am a detail-oriented Data Science student with hands-on experience in data annotation, quality assurance, and dataset validation for machine learning projects. My work includes curating, labeling, and reviewing both structured and unstructured datasets, with a focus on ensuring high accuracy and consistency through systematic QA checks. I am skilled in using Python (Pandas, NumPy), Excel, and familiar with annotation tools, as well as academic exposure to 2D/3D spatial data tools like QGIS and ArcGIS. I excel at identifying labeling inconsistencies, providing actionable feedback, and documenting workflows to optimize annotation processes. My strong analytical skills, attention to detail, and ability to collaborate with cross-functional teams help me deliver reliable, high-quality datasets that support robust AI model training.
converting audio to text, labelling who is speaking, tagging sounds and sounds.
categorized text data based on sentiment and topic. Worked on content moderation tasks.
object tracking with bounding boxes, segmentation labelling, object detection, scene classification and key point labelling.
Annotated images for object detection and bonding box projects. Labelled vehicles, pedestrians, and traffic signs for AI training datasets.
Bachelor of Science, Data Science
Donald S. hasn’t added any Work History to their OpenTrain profile yet.