Xin Lei Ng

Key Skills

Software

Appen

Clickworker

Top Subject Matter

General Visual Object Recognition

Speech Recognition

Top Data Types

Image

Audio

Top Task Types

Classification

Audio Recording

Freelancer Overview

Data Labeler. Brings 2+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Appen and Clickworker. Education includes Bachelor of Medical Bioscience, Monash University Malaysia (2023) and Bachelor of Science (Honours), Monash University Malaysia (2023). AI-training focus includes data types such as Image and Audio and labeling workflows including Classification and Audio Recording.

Labeling Experience

AI Data Trainer

ClickworkerAudioAudio Recording

As part of AI training with Clickworker, contributed by recording voice samples of phrases and sentences. Tasks were performed to provide diverse audio data for speech recognition model training. The role also included organizing, categorizing, and evaluating audio samples. • Participated in structured recording sessions. • Ensured clarity and correctness of all collected audio data. • Adhered to strict data privacy and quality standards. • Assisted in curating example prompts and responses for model improvement.

As part of AI training with Clickworker, contributed by recording voice samples of phrases and sentences. Tasks were performed to provide diverse audio data for speech recognition model training. The role also included organizing, categorizing, and evaluating audio samples. • Participated in structured recording sessions. • Ensured clarity and correctness of all collected audio data. • Adhered to strict data privacy and quality standards. • Assisted in curating example prompts and responses for model improvement.

2024 - Present

Data Labeler

AppenImageClassification

Data labeling at Appen involved annotating diverse objects from images according to provided descriptions. Tasks required careful attention to detail to accurately identify and classify targets such as cars or people. The work contributed to improving AI models by expanding labeled datasets. • Followed detailed guidelines to ensure consistency. • Maintained a high throughput of labeled images per hour. • Adapted to a variety of annotation tasks and objects. • Collaborated with remote teams for quality assurance.

Data labeling at Appen involved annotating diverse objects from images according to provided descriptions. Tasks required careful attention to detail to accurately identify and classify targets such as cars or people. The work contributed to improving AI models by expanding labeled datasets. • Followed detailed guidelines to ensure consistency. • Maintained a high throughput of labeled images per hour. • Adapted to a variety of annotation tasks and objects. • Collaborated with remote teams for quality assurance.

2020 - 2020

Education

Work History