Roseline Chinedu

Key Skills

Software

Clickworker

Data Annotation Tech

Label Studio

Mindrift

Telus

Top Subject Matter

No subject matter listed

Top Data Types

Image

Text

Video

Top Task Types

Classification

Evaluation Rating

Fine Tuning

Text Generation

Text Summarization

Freelancer Overview

As a seasoned data annotation specialist, I've developed expertise in labeling diverse data types, including images, videos, and text, to train and evaluate AI models. My experience spans various applications, from computer vision to natural language processing, with a focus on ensuring high-quality training data that drives accurate model performance. I've worked on multiple projects, annotating data for object detection, image classification, and conversational AI systems, with a keen eye for detail and a commitment to meeting project requirements.

Labeling Experience

Data Labeling

ClickworkerVideoClassificationEmotion Recognition

I worked on a video labeling project focused on analyzing human behavior in video content. My tasks included tracking movements, identifying actions (e.g., walking, sitting), and recognizing facial expressions and gestures. I also labeled human-object interactions, such as using a phone and wearing protective gear. Over a two-month period, our team annotated more than 10,000 video clips, consistently following detailed guidelines to ensure high accuracy. I maintained a quality score above 95% and participated in regular feedback sessions and peer reviews to support consistency and reliability across the project.

I worked on a video labeling project focused on analyzing human behavior in video content. My tasks included tracking movements, identifying actions (e.g., walking, sitting), and recognizing facial expressions and gestures. I also labeled human-object interactions, such as using a phone and wearing protective gear. Over a two-month period, our team annotated more than 10,000 video clips, consistently following detailed guidelines to ensure high accuracy. I maintained a quality score above 95% and participated in regular feedback sessions and peer reviews to support consistency and reliability across the project.

2025 - 2025

AI Response Evaluation

MindriftTextEvaluation Rating

The project involved evaluating and rating AI responses generated by a Large Language Model (LLM) to assess its performance and accuracy. I performed data labeling tasks, including text annotation (relevance, accuracy, and coherence scores), response rating (quality, relevance, and contextual appropriateness), and error annotation. The project consisted of approximately 80 text samples with multiple AI-generated responses. To ensure high-quality annotations, we implemented quality measures such as annotator training, inter-annotator agreement, and quality checks, which ensured consistency, accuracy, and adherence to project guidelines, ultimately improving the LLM's performance.

The project involved evaluating and rating AI responses generated by a Large Language Model (LLM) to assess its performance and accuracy. I performed data labeling tasks, including text annotation (relevance, accuracy, and coherence scores), response rating (quality, relevance, and contextual appropriateness), and error annotation. The project consisted of approximately 80 text samples with multiple AI-generated responses. To ensure high-quality annotations, we implemented quality measures such as annotator training, inter-annotator agreement, and quality checks, which ensured consistency, accuracy, and adherence to project guidelines, ultimately improving the LLM's performance.

2024 - 2024

Education

Work History