Data Annotation



Involvement of Data Annotaion

Data annotation involves assigning labels to unstructured data and information to train machine learning models. Raw data can take diverse forms such as images, video, text, and audio. When meticulously labelled, high-quality data plays a crucial role in aiding supervised machine learning models in tasks such as object identification, sentiment analysis, and functionalities like speech recognition or autonomous driving.

Our Approch to Data Annotation

KPT tailored its data annotation services to meet the distinct requirements of the clients. Our primary labelling services concentrate on top-notch text annotation, video annotation, audio annotation, and image annotation. KPT’s team collaborate closely with clients to fine-tune their quality specifications through customized processes that ensure the validation of annotation work. A proficient team of subject matter experts ensures the swift turnaround of all annotation tasks.

Video Annotation:

Video annotation is the precise labelling of individual frames in a video, a crucial step in developing robust computer vision models. KPT excels in annotating key points, polygons, or bounding boxes, empowering machine learning models to understand movement, behaviour, and patterns. This process ensures a comprehensive grasp of visual data, facilitating advanced concepts like localization and object tracking. Elevate your computer vision applications with KPT's expert video annotation services.

Image Annotation:

Image annotation encompasses the task of labelling an image, employing a combination of human-powered efforts and, at times, computer-assisted assistance. This process holds significance in the development of computer vision models, particularly for tasks such as image segmentation, image classification, and object detection. The scope of image annotation can vary, ranging from annotating individual pixel groups within an image to assigning a single label for the entire image.

Audio Annotation:

Audio data, rich in dynamics, involves factors like language, speaker demographics, mood, and more. KPT's audio annotation services go beyond verbal cues, identifying parameters through timestamping and labelling. We capture non-verbal elements like silence, breaths, and background noise, providing a holistic understanding for applications like speech recognition and sentiment analysis. Trust KPT for thorough audio annotation, enhancing your machine learning systems' comprehension of diverse audio attributes.

Bounding Boxes:

Rectangular box annotation stands out as the most widely employed form of image annotation in the field of computer vision. KPT’s computer vision experts leverage this technique to depict objects and facilitate data training by using annotated images. This practice equips algorithms with the ability to identify and localize objects throughout the machine learning process.

Text Annotation:

In the field of machine learning, the precision of text annotation takes precedence at KPT. Our text annotation services enhance diverse datasets, encompassing customer feedback to social media mentions.
Experience the expertise of KPT's text annotation services, including:

Semantic Annotation:

Refine entities, products, and services through meticulous key phrase tagging. Our annotations ensure chatbots engage in conversations with nuanced relevance.

Intent Annotation:

Decode user intentions and linguistic nuances with precision. Our tagging strategies enable machine learning models to distinguish requests, commands, recommendations, and more.

Sentiment Annotation:

Uncover emotional layers within textual data. Our sentiment annotation services categorize text into positive, negative, or neutral sentiments, offering insights for sentiment analysis.

At KPT, we redefine text annotation, injecting professionalism and engagement into every labelled phrase. Trust us to reveal the nuanced context and sentiments embedded in your textual data.