The goal is to have pre-trained models that can jointly learn representations to support a broad range of downstream AI tasks, much in the way humans do today. We believe XYZ-code will enable us to fulfill our long-term vision: cross-domain transfer learning, spanning modalities and languages. At the intersection of all three, there’s magic-what we call XYZ-code as illustrated in Figure 1-a joint representation to create more powerful AI that can speak, hear, see, and understand humans better. In my role, I enjoy a unique perspective in viewing the relationship among three attributes of human cognition: monolingual text (X), audio or visual sensory signals, (Y) and multilingual (Z). As Chief Technology Officer of Azure AI Cognitive Services, I have been working with a team of amazing scientists and engineers to turn this quest into a reality. "At Microsoft, we have been on a quest to advance AI beyond existing techniques, by taking a more holistic, human-centric approach to learning and understanding.
Contextual input range: The range within the input document that was used to generate the summary text.Īs an example, consider the following paragraph of text:.A long document may be segmented so multiple groups of summary texts may be returned with their contextual input range. Summary texts: Abstractive summarization returns a summary for each contextual input range within the document.Abstractive summarization: Generates a summary that may not use the same words as those in the document, but captures the main idea.Positional information: The start position and length of extracted sentences.For example, if you request a three-sentence summary extractive summarization will return the three highest scored sentences.
Multiple returned sentences: Determine the maximum number of sentences to be returned.Document summarization ranks extracted sentences, and you can determine whether they're returned in the order they appear, or according to their rank. Rank score: The rank score indicates how relevant a sentence is to a document's main topic.They’re original sentences extracted from the input document’s content. Multiple extracted sentences: These sentences collectively convey the main idea of the document.Extractive summarization: Produces a summary by extracting salient sentences within the document.There are two types of document summarization this API provides: These features are designed to shorten content that could be considered too long to read. Abstractive summarization generates a summary with concise, coherent sentences or words which are not simply extract sentences from the original document. There are two general approaches to automatic summarization, both of which are supported by the API: extractive and abstractive.Įxtractive summarization extracts sentences that collectively represent the most important or relevant information within the original content. How-to guides contain instructions for using the service in more specific or customized ways.ĭocument summarization uses natural language processing techniques to generate a summary for documents.Quickstarts are getting-started instructions to guide you through making requests to the service.This documentation contains the following article types: You can easily get started with the service by following the steps in this quickstart. To simplify building and customizing your model, the service offers a custom web portal that can be accessed through the Language studio. The quality of the labeled data greatly impacts model performance. By creating a Custom Summarization project, developers can iteratively label data, train, evaluate, and improve model performance before making it available for consumption.
AUTO SUMMARIZE GENERATOR HOW TO
Use this article to learn more about this feature, and how to use it in your applications.Ĭustom Summarization enables users to build custom AI models to summarize unstructured text, such as contracts or novels. Summarization is one of the features offered by Azure Cognitive Service for Language, a collection of machine learning and AI algorithms in the cloud for developing intelligent applications that involve written language.
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