Michael O.

Key Skills

Software

Appen

Data Annotation Tech

Top Subject Matter

AI Data Labeling Specialist

AI Training Data Annotator

. AI Quality Assurance Analyst

Top Data Types

Computer Code Programming

Audio

Text

Top Task Types

Classification

Question Answering

Transcription

Evaluation/Rating

Red Teaming

Data Collection

Text Summarization

Freelancer Overview

I have experience contributing to AI training and data labeling projects involving text annotation, transcription, content moderation, and data classification. My work has focused on improving the accuracy and performance of machine learning models by ensuring high-quality labeled datasets, maintaining consistency across tasks, and following detailed project guidelines. I am skilled in handling large volumes of data accurately and efficiently while meeting strict deadlines. My background in ICT has strengthened my technical understanding of AI systems, digital tools, and data management processes. In addition to annotation and labeling, I have experience reviewing conversational content, identifying patterns, and applying quality assurance standards to ensure reliable outputs for AI development. I am detail-oriented, adaptable, and quick to learn new platforms and workflows. My strong communication skills, problem-solving ability, and commitment to delivering precise results make me effective in collaborative and remote AI training environments.

Labeling Experience

Audio & Speech Annotation

AudioTranscription

I worked on AI training and transcription projects through Appen, involving speech-to-text data collection, audio transcription, and linguistic annotation to improve automatic speech recognition and natural language processing models. The scope of the projects included processing conversational audio, reviewing speech recordings from diverse speakers and accents, and accurately converting spoken language into written text in accordance with detailed project guidelines. Tasks also involved timestamping, speaker identification, text normalization, and correcting transcription inconsistencies to ensure high-quality training data for AI systems. The projects involved handling large datasets consisting of hundreds of audio clips and transcription tasks completed within strict turnaround times. Quality measures included maintaining high transcription accuracy, following formatting and annotation standards, conducting self-review checks, and meeting project-specific quality benchmarks. Attention to detail, confidentiality, consistency, and adherence to linguistic guidelines were essential to achieving reliable outputs and supporting the development of accurate AI speech recognition models.

2024 - Present

Education

Work History