Kingsley Amedu

Key Skills

Software

Lionbridge

Telus

Other

Top Subject Matter

No subject matter listed

Top Data Types

Audio

Text

Video

Top Label Types

Audio Recording

Transcription

Classification

Question Answering

Evaluation Rating

Text Generation

Freelancer Overview

I am an experienced data annotation and AI training data specialist with a strong background in search engine evaluation, transcription, and natural language processing tasks. My work as a Personalized Internet Assessor and Online Data Analyst involved rating content relevance, evaluating search engine quality, and ensuring the accuracy and fluency of AI-generated responses. I have hands-on experience transcribing audio, validating text-to-speech outputs, and assessing both the linguistic and technical quality of data for AI models. My attention to detail and linguistic sensitivity, developed through both my technical roles and my experience as an English language tutor, enable me to deliver high-quality, reliable datasets for machine learning and AI projects. I am skilled in audio and text data annotation, search quality rating, and upholding strict data handling protocols, making me a valuable contributor to any AI-driven initiative.

Labeling Experience

Video Labeller

OtherVideoText Generation

I work as a Video Labeller for Atlas Capture. The scope of the project involves annotating video data to support the development and improvement of AI models for visual recognition, motion tracking, and object detection. On a daily basis, I annotate video frames by labeling objects, actions, and movements according to project-specific guidelines. I identify and track objects across consecutive video frames to ensure temporal consistency. I apply bounding boxes, tags, or classifications to video content to support machine learning training. I also review and correct annotations to ensure accuracy and alignment with annotation standards. The project involves large volumes of video data with multiple video sequences and thousands of frames to annotate over the course of the assignment.

I work as a Video Labeller for Atlas Capture. The scope of the project involves annotating video data to support the development and improvement of AI models for visual recognition, motion tracking, and object detection. On a daily basis, I annotate video frames by labeling objects, actions, and movements according to project-specific guidelines. I identify and track objects across consecutive video frames to ensure temporal consistency. I apply bounding boxes, tags, or classifications to video content to support machine learning training. I also review and correct annotations to ensure accuracy and alignment with annotation standards. The project involves large volumes of video data with multiple video sequences and thousands of frames to annotate over the course of the assignment.

2025

Personalized Internet Assessor and AI Trainer

TelusTextClassificationQuestion Answering

I worked on multiple AI data evaluation and training projects with TELUS Digital supporting search engine optimization, content relevance assessment and AI model training. The projects focused on improving search engine performance and natural language understanding by providing human judgments on content relevance, language quality, and AI-generated responses with an emphasis on locale-specific and culturally appropriate results. The work involved large scale evaluation tasks consisting of numerous search queries, AI-generated responses and content samples reviewed on a daily basis. The projects spanned extended periods and contributed to continuously updated datasets used to train and refine search engines and AI language models. I had to strictly adhere to TELUS Digital’s detailed evaluation guidelines and rating criteria and consistently apply relevant scales and quality metrics across all tasks. Regular quality audits and feedback cycles were used to maintain high accuracy.

I worked on multiple AI data evaluation and training projects with TELUS Digital supporting search engine optimization, content relevance assessment and AI model training. The projects focused on improving search engine performance and natural language understanding by providing human judgments on content relevance, language quality, and AI-generated responses with an emphasis on locale-specific and culturally appropriate results. The work involved large scale evaluation tasks consisting of numerous search queries, AI-generated responses and content samples reviewed on a daily basis. The projects spanned extended periods and contributed to continuously updated datasets used to train and refine search engines and AI language models. I had to strictly adhere to TELUS Digital’s detailed evaluation guidelines and rating criteria and consistently apply relevant scales and quality metrics across all tasks. Regular quality audits and feedback cycles were used to maintain high accuracy.

2021 - 2025

Transcriptionist and Text-to-Speech (TTS) Specialist

OtherAudioAudio RecordingTranscription

I worked on transcription and text-to-speech (TTS) data labeling projects with Intron Voice AI, contributing to the development and improvement of speech recognition and speech synthesis models. The project involved converting raw audio data into high-quality, structured text datasets and evaluating synthesized speech outputs to ensure naturalness, accuracy, and linguistic consistency. The data supported machine learning models focused on African-accented English and multilingual speech. On the project, I labeled and corrected speech data including speaker identification, timestamps, and segmentation. I transcribed audio recordings into accurate, well-formatted text following strict transcription and annotation guidelines. I also reviewed and validated text-to-speech outputs by evaluating pronunciation, intonation, pacing and overall naturalness. The project involved large-scale audio datasets, consisting of hundreds of audio files across multiple speakers and recording conditions.

I worked on transcription and text-to-speech (TTS) data labeling projects with Intron Voice AI, contributing to the development and improvement of speech recognition and speech synthesis models. The project involved converting raw audio data into high-quality, structured text datasets and evaluating synthesized speech outputs to ensure naturalness, accuracy, and linguistic consistency. The data supported machine learning models focused on African-accented English and multilingual speech. On the project, I labeled and corrected speech data including speaker identification, timestamps, and segmentation. I transcribed audio recordings into accurate, well-formatted text following strict transcription and annotation guidelines. I also reviewed and validated text-to-speech outputs by evaluating pronunciation, intonation, pacing and overall naturalness. The project involved large-scale audio datasets, consisting of hundreds of audio files across multiple speakers and recording conditions.

2022 - 2023

Education

Work History