Christeen Adly

Key Skills

Software

Appen

Clickworker

Remotasks

Scale AI

Top Subject Matter

No subject matter listed

Top Data Types

Audio

Image

Text

Top Task Types

Audio Recording

Prompt Response Writing SFT

RLHF

Text Generation

Text Summarization

Freelancer Overview

I have substantial experience in data labeling and AI training data, having contributed to multiple projects on the Outlier platform. Notably, I participated in tasks such as Reinforcement Learning from Human Feedback (RLHF), where I evaluated and ranked AI-generated responses to enhance model alignment with human preferences. Additionally, I worked on projects like Kestrel Nexus, Xylophone Conversation, and Xylophone Echo, which involved tasks such as transcription, annotation, and quality assurance of Arabic audio data. These projects required meticulous attention to detail, adherence to specific guidelines, and a commitment to maintaining high-quality standards. Through these experiences, I have developed strong skills in data annotation, linguistic analysis, and the application of AI tools in real-world scenarios. My work has contributed to the improvement of AI models' performance and reliability, particularly in understanding and processing Arabic language data. I am adept at handling complex datasets and ensuring the accuracy and consistency necessary for effective AI training.

Labeling Experience

Xylophone Echo – Transcription of Egyptian Arabic Audio Recordings

Scale AIAudioEmotion RecognitionFine Tuning

In this project, I transcribed recorded conversations in Egyptian Arabic that were generated during the Xylophone Conversation phase. My tasks included accurate transcription, speaker identification, and ensuring alignment with formatting and punctuation standards. This work supported the development of Arabic speech recognition systems, requiring linguistic sensitivity, attention to dialectal details, and adherence to quality control measures.

In this project, I transcribed recorded conversations in Egyptian Arabic that were generated during the Xylophone Conversation phase. My tasks included accurate transcription, speaker identification, and ensuring alignment with formatting and punctuation standards. This work supported the development of Arabic speech recognition systems, requiring linguistic sensitivity, attention to dialectal details, and adherence to quality control measures.

2024 - 2024

Xylophone Conversation – Egyptian Arabic Audio Recording

Scale AIAudioData CollectionAudio Recording

This project involved recording natural friendly dialogues in Egyptian Arabic on assigned topics. Working with another speaker, I participated in natural conversation-style recordings. The goal was to create diverse, realistic audio data to support training of Arabic speech recognition and conversational AI models. Accuracy, clarity, and natural tone were essential, along with following topic guidelines and quality requirements.

This project involved recording natural friendly dialogues in Egyptian Arabic on assigned topics. Working with another speaker, I participated in natural conversation-style recordings. The goal was to create diverse, realistic audio data to support training of Arabic speech recognition and conversational AI models. Accuracy, clarity, and natural tone were essential, along with following topic guidelines and quality requirements.

2024 - 2024

Kestrel Nexus – AI Text Evaluation and Annotation

Scale AITextClassificationEvaluation Rating

I participated in evaluating AI-generated text for relevance and factual consistency. The task included scoring responses for clarity, coherence, and alignment with instructions. I followed detailed annotation guidelines to maintain consistency across batches and ensure high-quality training data for refining LLMs.

I participated in evaluating AI-generated text for relevance and factual consistency. The task included scoring responses for clarity, coherence, and alignment with instructions. I followed detailed annotation guidelines to maintain consistency across batches and ensure high-quality training data for refining LLMs.

2024 - 2024

RLHF (Reinforcement Learning from Human Feedback)

Scale AITextRLHFEvaluation Rating

In this project, I evaluated and ranked AI-generated text responses based on quality, helpfulness, and alignment with human intent. The task involved carefully comparing multiple model outputs and selecting the most appropriate one based on task-specific guidelines. My contributions helped improve model performance and safety in conversational AI systems. Accuracy, consistency, and attention to nuance were essential for ensuring data quality.

In this project, I evaluated and ranked AI-generated text responses based on quality, helpfulness, and alignment with human intent. The task involved carefully comparing multiple model outputs and selecting the most appropriate one based on task-specific guidelines. My contributions helped improve model performance and safety in conversational AI systems. Accuracy, consistency, and attention to nuance were essential for ensuring data quality.

2024 - 2024

Education

Work History