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Data Annotation

Data Annotation for Machine Learning and AI

Data annotation is the human-powered labeling of text, images, video, and audio to allow machine learning systems to recognize objects. Our global resources at Venga provide data annotation customized to your machine learning needs. We preprocess your data with metadata tags to make clean, usable data sets for your AI training programs.

Text Data Labeling

Beyond simple text strings, data labeling enriches your text with meta tags that provide the context, structure, and object recognition needed for AI training sets.

Text data labeling is a type of annotation in which meta tags identify parts of a text and add rich information for machine learning systems. These include linguistic annotation, entity annotation, and sentiment analysis. Venga discovers your custom labeling needs and provides human-powered annotations in over 75 languages.

Image and Video Annotation and Transcription

Improve your computer vision and pattern recognition solutions with quality human annotation of image data.

When public data sets are not enough, Venga provides customized image annotation. We offer annotation services including bounding boxes, semantic segmentation, image classification, and text transcription. With a global team working in over 75 languages, Venga provides clean, multilingual data for your machine learning systems.

Audio Annotation and Transcription

Transform your audio data into a simpler format that can be read and parsed by AI through transcription and annotation.

Text transcriptions and descriptive meta tags for your audio make it more usable for machine learning. Transcriptions allow AI systems and search engines to crawl your audio and understand it. Annotation provides richer information for your machine learning models.

Audio Classification

Classify audio data for improved natural language processing (NLP) in speech recognition, chatbots, text to speech, and voice search.

Audio classification is the process of analyzing audio data and categorizing it for use in machine learning. With in-country resources in over 75 languages, Venga meets your multilingual audio classification needs. Our human-based approach generates clean data sets to improve your natural language processing systems.

Sentiment & Intent Analysis

Categorize and annotate sentiment and intent in your text, voice, image, and video data with quality human analysis.

Intention and emotion can be a challenge for AI to understand. They often require large training sets of human-annotated sentiment data for reliable results. Such data sets include text analysis, social listening, emotion analysis, opinion mining, and language variations. Venga is a global company with in-country data analysis resourcing in over 75 languages to cover your multilingual sentiment analysis needs.