Claudine Burnley

Key Skills

Software

Labelbox

Top Subject Matter

No subject matter listed

Top Data Types

Image

Video

Audio

Top Label Types

Bounding Box

Point Key Point

Segmentation

Classification

Tracking

Emotion Recognition

Freelancer Overview

I am an AI training specialist with three years of hands-on experience in data labeling and annotation for image, video, and audio datasets. My work focuses on preparing high-quality training data for machine learning and computer vision models, with a strong emphasis on YOLO-based workflows. I am skilled in object detection, segmentation, classification, and multi-object tracking, and have extensive experience with industry-standard tools like Labelbox, CVAT, SuperAnnotate, and Remotasks. I excel at ensuring data quality through meticulous annotation, validation, and quality assurance processes, and I am adept at working with large, complex datasets. My background also includes audio transcription and labeling for speech recognition, and I am committed to meeting rigorous accuracy and productivity standards while collaborating effectively in remote environments.

Labeling Experience

AI Training & Multi-Modal Data Labeling Project (Images, Videos & Audio)

LabelboxAudioBounding BoxPoint Key Point

Worked on audio data labeling projects supporting the training of speech recognition, natural language processing (NLP), and AI models. Used industry-standard annotation tools such as CVAT and Labelbox for managing and reviewing audio datasets. Performed audio transcription, classification, and segmentation tasks, including labeling speech, non-speech events, and speaker-related attributes. Annotated datasets for emotion recognition, speech-to-text, and audio classification models, ensuring accurate and consistent labeling. Followed strict project guidelines and quality standards, conducting thorough quality assurance checks to maintain high transcription accuracy and annotation consistency. Efficiently processed large volumes of audio data while meeting productivity targets and deadlines. Collaborated remotely with project teams to address feedback, refine annotation outputs, and continuously improve dataset quality for AI training purposes.

Worked on audio data labeling projects supporting the training of speech recognition, natural language processing (NLP), and AI models. Used industry-standard annotation tools such as CVAT and Labelbox for managing and reviewing audio datasets. Performed audio transcription, classification, and segmentation tasks, including labeling speech, non-speech events, and speaker-related attributes. Annotated datasets for emotion recognition, speech-to-text, and audio classification models, ensuring accurate and consistent labeling. Followed strict project guidelines and quality standards, conducting thorough quality assurance checks to maintain high transcription accuracy and annotation consistency. Efficiently processed large volumes of audio data while meeting productivity targets and deadlines. Collaborated remotely with project teams to address feedback, refine annotation outputs, and continuously improve dataset quality for AI training purposes.

2024

AI Training & Multi-Modal Data Labeling Project (Images, Videos & Audio)

LabelboxVideoBounding BoxPoint Key Point

Worked on video data labeling projects for training computer vision and AI models, using industry-standard tools such as CVAT and Labelbox. Responsibilities included frame-by-frame video annotation, object detection, and multi-object tracking across short and long-form video sequences. Performed bounding box, polygon, and segmentation annotations to accurately label moving objects. Utilized tracking features in CVAT and Labelbox to maintain object identity across frames, ensuring temporal consistency throughout annotated videos. Prepared datasets in YOLO-compatible formats to support object detection and tracking models. Strictly followed project-specific annotation guidelines and quality standards, performing regular quality assurance checks to ensure accuracy, consistency, and completeness of labeled data. Efficiently handled large-scale video datasets while meeting productivity targets and deadlines. Collaborated remotely with cross-functional teams to incorporate feedback and co

Worked on video data labeling projects for training computer vision and AI models, using industry-standard tools such as CVAT and Labelbox. Responsibilities included frame-by-frame video annotation, object detection, and multi-object tracking across short and long-form video sequences. Performed bounding box, polygon, and segmentation annotations to accurately label moving objects. Utilized tracking features in CVAT and Labelbox to maintain object identity across frames, ensuring temporal consistency throughout annotated videos. Prepared datasets in YOLO-compatible formats to support object detection and tracking models. Strictly followed project-specific annotation guidelines and quality standards, performing regular quality assurance checks to ensure accuracy, consistency, and completeness of labeled data. Efficiently handled large-scale video datasets while meeting productivity targets and deadlines. Collaborated remotely with cross-functional teams to incorporate feedback and co

2024

AI Training & Multi-Modal Data Labeling Project (Images, Videos & Audio)

LabelboxImageBounding BoxPoint Key Point

Worked as an AI Training Specialist and Data Labeling Expert on large-scale datasets used to train and validate machine learning and computer vision models. Responsibilities included labeling and annotating images, videos, and audio data to support object detection, tracking, segmentation, and speech recognition tasks. Performed bounding box, polygon, and segmentation annotations on images and videos, including frame-by-frame video labeling and multi-object tracking. Prepared datasets in YOLO-compatible formats to ensure seamless model training. Annotated audio files through transcription and classification, supporting speech and emotion recognition models. Maintained high-quality standards by strictly following annotation guidelines, performing quality assurance checks, and ensuring accuracy, consistency, and completeness across datasets. Delivered high-volume annotations while meeting tight deadlines and productivity benchmarks.

Worked as an AI Training Specialist and Data Labeling Expert on large-scale datasets used to train and validate machine learning and computer vision models. Responsibilities included labeling and annotating images, videos, and audio data to support object detection, tracking, segmentation, and speech recognition tasks. Performed bounding box, polygon, and segmentation annotations on images and videos, including frame-by-frame video labeling and multi-object tracking. Prepared datasets in YOLO-compatible formats to ensure seamless model training. Annotated audio files through transcription and classification, supporting speech and emotion recognition models. Maintained high-quality standards by strictly following annotation guidelines, performing quality assurance checks, and ensuring accuracy, consistency, and completeness across datasets. Delivered high-volume annotations while meeting tight deadlines and productivity benchmarks.

2022 - 2024

Education

Work History