It helps with document classification and named entity extraction. It prepares training data for speech and voice models. It also covers 0 audio transcription, speaker diarization, and emotion recognition in audio. It's great for preparing training data for computer vision models. You can leverage 2 for time series analysis and event recognition. It also handles training data preparation for video models, and 3 for dialogue processing and optical character recognition. There's also 1 for question answering and sentiment analysis. It allows for the classification of images, audio, text, and time series data, and object detection and tracking in images and videos. It's useful for preparing training data for natural language processing models. And finally, it supports 4 multi-domain applications that need various types of data labeling.
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