Derrick Auma

Key Skills

Software

Appen

CVAT

Data Annotation Tech

Labelbox

Scale AI

Toloka

Top Subject Matter

No subject matter listed

Top Data Types

Audio

Computer Code Programming

Document

Image

Top Label Types

Audio Recording

Classification

Emotion Recognition

Evaluation Rating

Fine Tuning

Prompt Response Writing SFT

Question Answering

Transcription

Freelancer Overview

I bring over four years of experience in delivering high-quality voiceovers and audio content for a wide range of clients, including digital agencies, e-learning platforms, and corporate firms. My background in script editing, narration, and audio production has equipped me with a keen attention to detail and a strong ability to follow complex guidelines—skills essential for data labeling and AI training data roles. I am adept at managing large volumes of content, ensuring accuracy and consistency, and working independently to meet tight deadlines. My technical expertise includes advanced audio editing, annotation, and content adaptation using professional DAW software, making me well-suited for projects in natural language processing, speech recognition, and multimedia data annotation. I am fluent in both English (neutral and African accent) and Swahili, which allows me to contribute effectively to multilingual AI training datasets.

Labeling Experience

Speech Data Transcription & Audio Annotation Project

CVATAudioEmotion RecognitionPrompt Response Writing SFT

Contributed to an Education & E-learning speech data project involving high-accuracy audio transcription, emotion recognition, and annotation of student–tutor conversations. Developed structured prompt–response pairs (SFT) to support AI tutoring systems and conversational learning models. Ensured quality through detailed labeling, speaker identification, and adherence to annotation guidelines to enhance ASR and intelligent learning platforms.

Contributed to an Education & E-learning speech data project involving high-accuracy audio transcription, emotion recognition, and annotation of student–tutor conversations. Developed structured prompt–response pairs (SFT) to support AI tutoring systems and conversational learning models. Ensured quality through detailed labeling, speaker identification, and adherence to annotation guidelines to enhance ASR and intelligent learning platforms.

2021 - 2025

AI Conversation Annotation & Sentiment Labeling for Customer Support Systems

LabelboxAudioClassificationEvaluation Rating

Contributed to a large-scale conversational AI data labeling project focused on customer support automation. Annotated multi-turn conversations for sentiment, intent classification, and response quality evaluation. Performed transcription and structured prompt–response generation (SFT) to fine-tune large language models for improved customer interaction. Applied strict quality assurance processes to ensure annotation consistency, contextual accuracy, and alignment with training objectives for AI-powered support systems.

Contributed to a large-scale conversational AI data labeling project focused on customer support automation. Annotated multi-turn conversations for sentiment, intent classification, and response quality evaluation. Performed transcription and structured prompt–response generation (SFT) to fine-tune large language models for improved customer interaction. Applied strict quality assurance processes to ensure annotation consistency, contextual accuracy, and alignment with training objectives for AI-powered support systems.

2022 - 2023

Education

Work History