Chidera U.

Key Skills

Software

Don't disclose

Top Subject Matter

AI output evaluation and technical content quality assurance

Content classification

research evaluation frameworks

Top Data Types

Text

Audio

Document

Top Task Types

Data Collection

Classification

Freelancer Overview

I have practical experience with data annotation, AI output evaluation, and structured quality review in both technical and research-based projects. I have a degree in computer science. In my work, I have evaluated AI-generated content for accuracy, consistency, clarity, and formatting using comprehensive rubrics and evaluation guidelines. Additionally, I've worked on AI voice training and audio annotation projects, where I used annotation standards to record vocal characteristics, classify speech data, and label audio segments with timestamps. Alongside this, I have experience reviewing system-generated outputs, identifying inconsistencies, and producing structured reports that supported issue resolution and workflow improvements. What sets me apart is my strong attention to detail, analytical thinking, and ability to work independently in remote environments while maintaining high quality standards. Across previous roles, I’ve handled structured documentation, content classification, research synthesis, and error detection tasks, requiring precision and consistency. I’m also proficient with AI tools such as ChatGPT, Claude, and Gemini, and I’m comfortable adapting quickly to new annotation frameworks, taxonomies, and evaluation systems.

Labeling Experience

Audio Data Annotation and AI Voice Training — Perle Labs

Don't discloseAudioClassification

Completed structured audio annotation and evaluation tasks for AI voice training using detailed guidelines and annotation rubrics. Classified audio content into speech, noise, and music categories with precise temporal timestamps. Documented vocal characteristics including pitch, tone, pace, and volume using concise, style-compliant language. • Performed audio content categorization with timestamps. • Applied annotation rubrics for consistent labeling. • Labeled vocal characteristics for voice training datasets. • Produced structured annotation outputs following guideline-driven formats.

2025 - 2025

Education

Work History