Data is an integral part of all machine learning and deep learning algorithms, it can also be said that the algorithm is as good as the given data. In order to build truly reliable AI algorithms, one must provide properly structured and labeled data. We create high-quality, pixelwise, human-annotated data for your AI algorithms. There are several types of annotation for different desired outputs that we offer.
Audio annotation involves classifying components of audio that come from people, animals, the environment, instruments, and so on. Audio annotation is crucial for the development of virtual assistants, chatbots, voice recognition security systems, etc. It is vital in helping the machines process the sound that is present in the audio so that it could be easily understood and learned by the AI models in order to give accurate results.
Text annotation can help machine learning models understand text data. Common examples of text annotations are chatbots, part-of-speech tagging, sentiment analysis, etc. In the process of annotating text, the data is parsed into the required categories including phrases, sentences, and keywords, based on the guidelines of the project. The annotated text data trains the models to understand and communicate the natural language of humans.