Sharon Nyaema

Key Skills

Software

Labelbox

Top Subject Matter

No subject matter listed

Top Data Types

Video

Image

Top Label Types

Bounding Box

Point Key Point

Classification

Emotion Recognition

Tracking

Segmentation

Freelancer Overview

I am an AI training specialist with over three years of hands-on experience in video and audio data annotation, object detection, segmentation, and tracking for machine learning projects. My expertise includes preparing high-quality datasets, following complex labeling guidelines, and ensuring annotation accuracy through quality assurance processes. I am highly proficient with tools such as Labelbox, CVAT, Supervisely, VGG Image Annotator, and Audacity, and have experience working with object tracking and identification tools like YOLO. I excel at collaborating with technical teams to enhance dataset quality and model performance, and I thrive in fast-paced remote environments where attention to detail and productivity are essential. My strong problem-solving skills and ability to adapt quickly enable me to consistently deliver reliable results for AI and computer vision projects.

Labeling Experience

Video & Audio Annotation for Autonomous Driving & Speech Recognition Models

LabelboxAudioBounding BoxPoint Key Point

In this ongoing project, I am responsible for labeling and annotating audio data for a speech recognition model used in virtual assistants and voice-driven AI applications. The primary task involves transcribing and classifying spoken language into text to train natural language processing models. I work with large volumes of audio recordings, including conversations, commands, and varied accents to ensure comprehensive language model training. The project includes the following key tasks: Audio Transcription: Converting spoken words from audio files into accurate text, ensuring punctuation, context, and proper noun recognition. Speech Recognition Annotation: Tagging different types of speech such as commands, questions, and conversational speech to train the AI to better understand natural language. Emotion & Tone Detection: Annotating speech patterns to help the model recognize and understand emotions (e.g., happy, angry, neutral). Speaker Identification: Labeling different spea

In this ongoing project, I am responsible for labeling and annotating audio data for a speech recognition model used in virtual assistants and voice-driven AI applications. The primary task involves transcribing and classifying spoken language into text to train natural language processing models. I work with large volumes of audio recordings, including conversations, commands, and varied accents to ensure comprehensive language model training. The project includes the following key tasks: Audio Transcription: Converting spoken words from audio files into accurate text, ensuring punctuation, context, and proper noun recognition. Speech Recognition Annotation: Tagging different types of speech such as commands, questions, and conversational speech to train the AI to better understand natural language. Emotion & Tone Detection: Annotating speech patterns to help the model recognize and understand emotions (e.g., happy, angry, neutral). Speaker Identification: Labeling different spea

2020 - 2023

High-Volume Video Object Detection & Multi-Object Tracking for Computer Vision Model Training

LabelboxImageBounding BoxPoint Key Point

Contributed to a large-scale image annotation project designed to train and optimize computer vision models for object detection and segmentation tasks.

Contributed to a large-scale image annotation project designed to train and optimize computer vision models for object detection and segmentation tasks.

2023

High-Volume Video Object Detection & Multi-Object Tracking for Computer Vision Model Training

LabelboxVideoBounding BoxPoint Key Point

Worked on a large-scale computer vision project focused on training and improving object detection and multi-object tracking models for real-world video environments

Worked on a large-scale computer vision project focused on training and improving object detection and multi-object tracking models for real-world video environments

2021 - 2023

Education

Work History