AppTek Expands Workbench Data Labeling and Annotation Platform

AppTek, a provider of artificial intelligence (AI), automatic speech recognition (ASR), neural machine translation (NMT), text-to-speech (TTS), and natural language processing/understanding (NLP/U) technologies, has expanded its Workbench data labeling and annotation platform to include video labeling capabilities for computer vision models, in addition to its ASR, NMT, TTS, and NLP/U data services.

To create the robust data sets required for high-performing AI models, AppTek employs its proprietary Workbench, a secure, cloud-based data annotation and labeling tool that plugs into any data supply chain and fuses the human-machine relationship to produce high quality data and generate custom ML data sets for AI models.

Now AppTek expands its portfolio of data offerings to include the labelling of data for video tasks and the creation of multimodal speech/video models with the addition of computer vision (CV) engines powered by partner IDenTV. These computer vision classifiers combine with AppTek's automatic speech recognition AI models to optimize and scale the data labelling and annotation workflow. By combining large amounts of multi-format and multi-domain audio, text and image data,  ustomers can deploy bespoke models for new and innovative AI offerings.

"As federal and enterprise customers move rapidly to adopt AI, time and cost efficiencies are critical," said Katie Nguyen, senior vice president of data operations at AppTek, in a statement. "The complexity involved to ingest, label, and annotate large amounts of multiformat audio, text, and video data makes the process costly and time-consuming. By supplementing AppTek's high-performing speech and language models with video annotation capabilities, we can now deliver a new portfolio of scientifically tested and validated data sets at a fraction of the time it would take for manual annotation and at significantly less cost."

"AppTek has teamed with system integrators and leading industry partners to optimize data science workflows with backend AI models for computer vision classifiers and automatic speech recognition to drive the Workbench platform," said AppTek CEO Mudar Yaghi in a statement.. "We continue to focus on speed to value for our customers, and these new enhancements to the Workbench will drive even more efficiencies and cost savings."

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