Manasseh I.

Key Skills

Software

Appen

Telus

Top Subject Matter

Speech and audio evaluation

language annotation for AI training

AI data evaluation

Top Data Types

Audio

Top Task Types

Transcription

Evaluation/Rating

Classification

Data Collection

RLHF

Prompt + Response Writing (SFT)

Text Generation

Question Answering

Text Summarization

Freelancer Overview

Data Labeling & AI Training Contributor, Appen (Remote). Brings 11+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Appen and Telus. Education includes Bachelor of Arts, University of Benin. AI-training focus includes data types such as Audio and labeling workflows including Evaluation and Rating.

Labeling Experience

Data Labeling & AI Training Contributor, Appen (Remote)

AppenAudio

Labeled, reviewed, and evaluated audio and language data for AI and machine learning training projects following strict annotation guidelines. Reviewed speech recordings and assigned quality-related labels for clarity, accent, and pronunciation. Categorized and checked data accuracy, relevance, and quality before submission. • Labeled and evaluated speech/audio recordings for quality and intelligibility • Assessed Nigerian English speech patterns to support speech recognition improvement • Followed project-specific instructions, rating systems, and consistency requirements • Performed guideline-based QC checks prior to data release

2021 - 2025

AI Data Analyst / Language Evaluator, TELUS (Remote)

TelusAudio

Performed AI data evaluation, annotation, and quality review by comparing audio, text, and language samples for accuracy and naturalness. Rated data based on relevance, clarity, correctness, and usefulness while applying detailed project guidelines. Identified errors, inconsistencies, and low-quality content and provided structured feedback to support AI training. • Rated language and AI-related data for relevance, clarity, and correctness • Reviewed language content to improve AI model understanding and response quality • Flagged inconsistencies and low-quality samples during review tasks • Provided human judgment and structured feedback for training datasets

2016 - 2024

Education

Work History