Natural language processing (NLP) is a branch of artificial intelligence that helps computers understand, interpret and manipulate human language. NLP draws from many disciplines, including computer science and computational linguistics, in its pursuit to fill the gap between human communication and computer understanding.
Natural language processing helps computers communicate with humans in their own language and scales other language-related tasks. For example, NLP makes it possible for computers to read text, hear speech, interpret it, measure sentiment and determine which parts are important.
Today’s machines can analyze more language-based data than humans, without fatigue and in a consistent, unbiased way. Considering the staggering amount of unstructured data that’s generated every day, from medical records to social media, automation will be critical to fully analyze text and speech data efficiently.
• Content categorization. A linguistic-based document summary, including search and indexing, content alerts and duplication detection.
• Topic discovery and modeling. Accurately capture the meaning and themes in text collections, and apply advanced analytics to text, like optimization and forecasting.
• Contextual extraction. Automatically pull structured information from text-based sources.
• Sentiment analysis. Identifying the mood or subjective opinions within large amounts of text, including average sentiment and opinion mining.
• Speech-to-text and text-to-speech conversion. Transforming voice commands into written text, and vice versa.
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