Anna Frey

Key Skills

Software

Appen

Top Subject Matter

No subject matter listed

Top Data Types

Audio

Image

Text

Top Label Types

Classification

Evaluation Rating

Freelancer Overview

I have hands-on experience as an AI Data Evaluator, where I assess human–voice assistant interactions and evaluate AI response accuracy, relevance, and naturalness to support conversational AI training and performance improvement. My background in qualitative research and discourse analysis, combined with practical experience in data administration and project management across startup and customer service environments, enables me to approach data annotation and labeling tasks with strong attention to detail and a deep understanding of human communication patterns. I am proficient in CRM and booking systems, experienced in multilingual environments (Finnish, English, Swedish), and comfortable delivering quality assurance in fast-paced, dynamic settings. My academic focus on social sciences and communication further strengthens my ability to contribute to high-quality AI training data projects, particularly in NLP and user experience domains.

Labeling Experience

Hazel v2 – Voice Assistant Data Evaluations

AppenTextClassificationEvaluation Rating

Evaluating human–voice assistant interactions as part of Appen's Hazel v2 Data Evaluations project. Working with multiple data types including audio, image, and text. Tasks involve assessing spoken factuality, response completeness, transcription accuracy (ASR hypothesis verification), and image-based query evaluation. Focusing on AI response accuracy, relevance, and naturalness across multiple criteria to contribute to conversational AI training and performance improvement.

Evaluating human–voice assistant interactions as part of Appen's Hazel v2 Data Evaluations project. Working with multiple data types including audio, image, and text. Tasks involve assessing spoken factuality, response completeness, transcription accuracy (ASR hypothesis verification), and image-based query evaluation. Focusing on AI response accuracy, relevance, and naturalness across multiple criteria to contribute to conversational AI training and performance improvement.

2025

Education

Work History