Lindarose A.

Key Skills

Software

Don't disclose

Other

Top Subject Matter

AI/ML training datasets and research data

Voice data collection and AI voice training

Image annotation for AI/ML datasets

Top Data Types

Text

Audio

Image

Top Task Types

Classification

Audio Recording

Segmentation

Entity (NER) Classification

Freelancer Overview

Data annotation and data labeling (text) for AI/ML support. Professional background includes roles such as Virtual Assistant & Research Specialist. Core strengths include Don't disclose. AI-training focus includes data types such as Text, Audio, and Image and labeling workflows including Classification, Audio Recording, and Segmentation.

Labeling Experience

Image annotation and dataset labeling support

Don't discloseImageSegmentation

Contributed to image annotation efforts by applying text, image, and related labeling tasks to improve dataset usefulness. Focused on accurate labeling and maintaining dataset integrity for machine learning applications. Supported quality assurance activities to reduce errors and improve annotation reliability. • Participating in image labeling and related annotation tasks • Ensuring labels meet quality expectations • Supporting dataset preparation for ML training • Performing error-checking as part of QA

2025 - Present

Voice data collection and voice training support

OtherAudioAudio Recording

Supported voice training workflows by assisting with voice data collection and evaluation for AI systems. Contributed to organizing and preparing voice-related training materials to meet processing and quality requirements. Ensured selected samples aligned with training objectives for accurate model development. • Assisting with voice data collection • Evaluating voice data for training suitability • Preparing voice datasets for AI systems • Supporting quality control during voice training

2025 - Present

Data annotation and data labeling (text) for AI/ML support

OtherTextClassificationEntity (NER) Classification

Performed data annotation by reviewing, tagging, and categorizing text-based records to support machine learning and AI improvements. Validated and cross-checked dataset entries to ensure labels matched required categories and quality standards. Helped maintain accurate and well-organized datasets for downstream digital projects. • Tagging and categorization of dataset items • Dataset validation and accuracy checks • Maintaining labeling quality and consistency • Supporting research-oriented data management

2025 - Present

Education

Work History