Ontologies include information like annotation types, labeling guidelines, and class and attribute standards. Ontologies: Think of ontologies as the blueprints to provide accurate and helpful annotation frameworks.In every type of data annotation, a few key tools help make annotation possible: Video annotation has become particularly important in the development of technologies like self-driving cars and in-home IoT devices. Video annotation combines several features of image and audio annotation, helping AI to assess the meaning of sound and visual elements in a video clip. More on this topic: The Conversational AI Revolution: The Threat and the Opportunity Video annotation IoT devices like home assistants rely on the speech and audio recognition that comes from audio annotation. Audio annotators handle raw data in the form of speech and other sound effects, and then they label and categorize audio clips based on qualities like pronunciation, intonation, dialect, and volume, among others. Many mobile and Internet of Things (IoT) devices rely on speech recognition and other audio comprehension features, but they only learn audial meanings through the practice of audio annotation. Image annotation has expanded AI capabilities over the years, now adding contextual annotations to detailed images of streets and human bodies, which provide training data for self-driving vehicles and medical diagnostic tools. Image annotation makes images accessible to users who use screen readers, and it also helps websites like stock image aggregators identify and deliver photos for user queries.
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