Nouhayla Hasnaouy

Key Skills

Software

CVAT

LabelImg

Label Studio

Other

Top Subject Matter

No subject matter listed

Top Data Types

Audio

Document

Image

Top Task Types

Classification

Emotion Recognition

Evaluation Rating

Text Generation

Text Summarization

Freelancer Overview

Data Labeling and AI Training SpecialistI’m a detail-oriented professional with hands-on experience in annotating and labeling datasets, including text, audio, and images, to support machine learning model development. Skilled in using tools like Label Studio and Taguette, I deliver accurate and consistent data annotations that meet project needs. My proficiency in Arabic, French, English, Spanish, and Turkish allows me to work with multilingual datasets, adding versatility to AI projects.I’m committed to ensuring data quality through careful review processes and enjoy collaborating with teams to understand project goals and improve annotation guidelines. Adaptable and dependable, I thrive in dynamic settings and am eager to contribute to the success of AI training initiatives with my strong work ethic.

Labeling Experience

Transcription for Voice Command Recognition

OtherAudioTranslation Localization

I annotated 1,200 audio clips in Arabic, Turkish, and French to train a voice assistant for a tech startup. My responsibilities included transcribing spoken commands, labeling audio quality (e.g., clear, accented, background noise), and translating select phrases for localization. I followed strict protocols to handle regional dialects and performed quality reviews, achieving a 95% transcription accuracy rate. My multilingual proficiency was key to managing diverse audio data, and I provided feedback to improve guidelines for ambiguous recordings.

I annotated 1,200 audio clips in Arabic, Turkish, and French to train a voice assistant for a tech startup. My responsibilities included transcribing spoken commands, labeling audio quality (e.g., clear, accented, background noise), and translating select phrases for localization. I followed strict protocols to handle regional dialects and performed quality reviews, achieving a 95% transcription accuracy rate. My multilingual proficiency was key to managing diverse audio data, and I provided feedback to improve guidelines for ambiguous recordings.

2025 - 2025

Image Annotation for Retail Product Recognition

CVATImageBounding BoxClassification

I worked on annotating product images to train a computer vision model for a retail inventory management system. My role involved drawing bounding boxes around items like clothing, electronics, and household goods, and classifying product categories (e.g., shirts, laptops, kitchenware). The project required adherence to strict guidelines to ensure consistency across diverse product types. I conducted regular quality checks, achieving a 93% accuracy rate, and provided feedback to streamline ambiguous category definitions.

I worked on annotating product images to train a computer vision model for a retail inventory management system. My role involved drawing bounding boxes around items like clothing, electronics, and household goods, and classifying product categories (e.g., shirts, laptops, kitchenware). The project required adherence to strict guidelines to ensure consistency across diverse product types. I conducted regular quality checks, achieving a 93% accuracy rate, and provided feedback to streamline ambiguous category definitions.

2023 - 2024

Text Annotation for Chatbot Training

Label StudioTextEntity Ner ClassificationClassification

I annotated a dataset of 2000 customer support queries in English and French to train a chatbot for a retail company. My role involved classifying user intents (refund request, product inquiry, complaint) and tagging named entities like product names and dates. I followed detailed guidelines to ensure consistent labeling and participated in weekly team reviews to maintain quality, achieving a 96% accuracy rate. My bilingual skills helped streamline annotations across both languages, and I provided feedback to clarify ambiguous intent categories, improving the annotation process.

I annotated a dataset of 2000 customer support queries in English and French to train a chatbot for a retail company. My role involved classifying user intents (refund request, product inquiry, complaint) and tagging named entities like product names and dates. I followed detailed guidelines to ensure consistent labeling and participated in weekly team reviews to maintain quality, achieving a 96% accuracy rate. My bilingual skills helped streamline annotations across both languages, and I provided feedback to clarify ambiguous intent categories, improving the annotation process.

2023 - 2023

Education

Work History