Audio Classification

The rapid increase of information imposes new demands for content management. The goal of audio classification is to meet the rising need for efficient audio content management. Audio classification which is also known as sound classification is the process of listening and analysing audio files or recordings to classify them under relevant categories, depending upon the content in them. It is an integral part of many AI-based technologies like automatic speech recognition, virtual assistants and text to speech applications. Machines require large sets of annotated audio data to learn, understand and differentiate between various types of sounds. The classification of audio files is a part of the annotation process and this classification of audio data is done based on project-specific needs. Companies often prefer dedicated audio classification services for their classification needs. Outsourcing audio classification project allows to avail the services of professionals and experts. Outsourcing also reduces overall project cost and saves time & resources.

Video Classification

Video Classification is the task of producing a label that is relevant to the video given its frames. A good video level classifier is one that not only provides accurate frame labels, but also best describes the entire video given the features and the annotations of the various frames in the video. For example, a video might contain a tree in some frame, but the label that is central to the video might be something else (e.g., “hiking”). The granularity of the labels that are needed to describe the frames and the video depends on the task. Typical tasks include assigning one or more global labels to the video, and assigning one or more labels for each frame inside the video. We can provide these Services.

Image Classification

Image classification is the task of assigning a label or class to an entire image. Images are expected to have only one class for each image. Image classification models take an image as input and return a prediction about which class the image belongs to.

Image classification models can be used when we are not interested in specific instances of objects with location information or their shape. Image classification models are used widely in stock photography to assign each image a keyword. Models trained in image classification can improve user experience by organizing and categorizing photo galleries on the phone or in the cloud, on multiple keywords or tags.

Our classification services classify your images into the requested categories. Labelling different types of animals is one example of image classification. In such a project the annotators’ task would be to classify the images of different animals based on their species.

Text Classification

Data is the new asset of businesses operating today. There are multiple sources of data like chat conversations, websites, emails and social media platforms. But most of this data is unstructured, so it’s difficult to extract any value from this data. To make this data useful it has to be organised or classified in a certain way. Categorizing textual data into organised groups called categories is known as text classification. Text classification is also known as text categorization or text tagging. Text classification is a very time consuming, cumbersome and expensive process if it is done manually. By using Natural Language Processing (NLP), machine learning algorithms can automatically analyze the text and then organize it into different categories by assigning it pre-defined tags.

ML-based models which use NLP for text classification perform fast, cost-effective, and scalable text classification solutions. But before these ML algorithms can efficiently classify voluminous text datasets, they need to be exhaustively trained for this purpose. Large quantities of high-quality human-annotated training data are required to make ML algorithms understand various forms of text and also intent and sentiments within it. We provides text classification services, with high-quality training data to train your natural language processing based ML-algorithms. Accurate annotation services offered by us, train your NLP based ML algorithms to automatically classify your text data sets into relevant categories.