Tekipharm

Key Skills

Software

Appen

Telus

Other

Top Subject Matter

No subject matter listed

Top Data Types

Audio

Document

Geospatial Tiled Imagery

Image

Medical Dicom

Text

Video

Top Label Types

Action Recognition

Audio Recording

Bounding Box

Classification

Data Collection

Emotion Recognition

Evaluation Rating

Object Detection

Point Key Point

Prompt Response Writing SFT

Question Answering

Text Generation

Text Summarization

Transcription

Translation Localization

Freelancer Overview

I am an experienced English Voice Coach and Audio Quality Analyst specializing in data annotation and AI training data for voice and linguistic projects. My background includes analyzing and annotating short audio recordings for tone, pitch, clarity, and emotional expressiveness, as well as performing linguistic QA on both human and AI-generated audio. I am adept at providing structured feedback, ensuring annotation consistency, and refining guidelines for improved data quality. With advanced proficiency in English (C2) and fluency in French, I have worked across diverse datasets, including telehealth and multilingual contexts, and am skilled at identifying subtle vocal and linguistic nuances. My experience in remote, detail-oriented environments has equipped me to deliver high-quality results in speech and audio data labeling projects.

Labeling Experience

Freelance Linguistic QA Analyst – Classik Voices

TelusTextEvaluation Rating

Performed linguistic and logical quality assurance on AI-generated content and evaluation scenarios. Reviewed realism, tone consistency, and clarity of AI responses, flagging ambiguity and logical risks. Supported multilingual dataset evaluation and improved quality through structured annotation and reviewer feedback. • Evaluated English and French datasets for consistency and clarity • Flagged ambiguity, logical gaps, and risks in scenarios • Used reviewer tools and frameworks for QA annotation • Iteratively improved dataset quality with clear feedback

Performed linguistic and logical quality assurance on AI-generated content and evaluation scenarios. Reviewed realism, tone consistency, and clarity of AI responses, flagging ambiguity and logical risks. Supported multilingual dataset evaluation and improved quality through structured annotation and reviewer feedback. • Evaluated English and French datasets for consistency and clarity • Flagged ambiguity, logical gaps, and risks in scenarios • Used reviewer tools and frameworks for QA annotation • Iteratively improved dataset quality with clear feedback

2024

Freelance AI Evaluation Analyst / AI Data Specialist

AppenTextEvaluation Rating

Reviewed and evaluated AI-generated tasks, scenarios, and prompts for logical accuracy, realism, and completeness. Identified contradictions, unclear assumptions, and unrealistic constraints in structured task structures. Annotated reasoning paths and conducted pairwise comparisons to improve evaluation coverage. • Performed evaluation and annotation using platforms such as Telus, RWS, Appen, and OneForma • Focused on large language model outputs and autonomous agent behaviors • Interpreted structured data (e.g., JSON) to guide labeling and assessment • Delivered feedback to improve evaluation frameworks and data quality

Reviewed and evaluated AI-generated tasks, scenarios, and prompts for logical accuracy, realism, and completeness. Identified contradictions, unclear assumptions, and unrealistic constraints in structured task structures. Annotated reasoning paths and conducted pairwise comparisons to improve evaluation coverage. • Performed evaluation and annotation using platforms such as Telus, RWS, Appen, and OneForma • Focused on large language model outputs and autonomous agent behaviors • Interpreted structured data (e.g., JSON) to guide labeling and assessment • Delivered feedback to improve evaluation frameworks and data quality

2021

Education

Work History