Anthonia Olorundare

Key Skills

Software

Scale AI

Top Subject Matter

No subject matter listed

Top Data Types

Audio

Top Label Types

RLHF

Freelancer Overview

I am a detail-oriented data evaluator and virtual assistant with hands-on experience in data annotation, linguistic analysis, and AI content refinement. My background includes labeling and categorizing audio data to train and enhance Text-to-Speech models, with a strong focus on phonetics, tone, and pacing in both English and Yoruba. I have managed complex workflows using collaborative tools like Slack and Trello, and am skilled in quality assurance—identifying unnatural cadences and refining AI outputs for more natural speech synthesis. My work as a content lead for AI-generated video content has further strengthened my ability to select, review, and optimize AI voiceovers for clarity and emotional resonance. I am passionate about contributing to projects that require high-quality training data and nuanced linguistic oversight for AI and machine learning applications.

Labeling Experience

AI Voice Synthesis Evaluation & Text-to-Audio Alignment (Bible Storytelling)

Scale AIAudioRLHF

Lead evaluator for an AI-driven YouTube channel focused on cinematic biblical storytelling. My role involves generating and labeling high-quality synthetic audio data to ensure emotional resonance and linguistic accuracy. Core tasks include: Audio Evaluation: Rating AI-generated voiceovers for prosody, naturalness, and "human-like" inflection across diverse character profiles (e.g., Jonah, Ninevites). Text-to-Audio Alignment: Verifying that AI outputs accurately reflect complex script prompts and biblical terminology. Quality Control: Identifying and flagging "robotic" artifacts, mispronunciations, and pacing issues to refine the final output. Prompt Engineering: Iterating on text-based instructions to improve the specific vocal tone (cinematic, urgent, reflective) of the AI model.

Lead evaluator for an AI-driven YouTube channel focused on cinematic biblical storytelling. My role involves generating and labeling high-quality synthetic audio data to ensure emotional resonance and linguistic accuracy. Core tasks include: Audio Evaluation: Rating AI-generated voiceovers for prosody, naturalness, and "human-like" inflection across diverse character profiles (e.g., Jonah, Ninevites). Text-to-Audio Alignment: Verifying that AI outputs accurately reflect complex script prompts and biblical terminology. Quality Control: Identifying and flagging "robotic" artifacts, mispronunciations, and pacing issues to refine the final output. Prompt Engineering: Iterating on text-based instructions to improve the specific vocal tone (cinematic, urgent, reflective) of the AI model.

2025

Education

Work History