Natual language processing can be used for many applications. Below we list some of these and hints on which NLP APIs can be used for each task.
Reading thru large amounts of text can be time-consuming and thus it is beneficial to have a short summary of the content.
With natural language processing methods it is possible to automate the summary generation and get summaries much faster than when a human writes the summary.
The basic principle of an search engine is to find entries in the search index that match the search query. If matching is done simply by looking for exact matches then the search will fail if the query or the entries use different inflected form of the word.
Knowledge is power and texts can contain all sorts of interesting information. But if there are large amounts of text, reading thru all that is time-consuming.
Research on human languages can reveal all sorts of interesting details about languages and their use. And when you want to know about the real-life language usage, the common approach is to find occurences of specific linguistic phenomena within text corporas.
A machine translation system aims to find the corresponding expressions in target language for the expressions in the source language.
Linguistic analysis can be beneficial in understanding the structure of the source language input and then determine the corresponding translation.
Understanding what sentiments people have towards certain products, services, persons, locations and so on can be interesting information.
With natural language processing methods it is possible to extract this sort of information from texts.
Speech recognition software attempts to decipher the spoken language into form that computers understands.
Natural language processing can be used to create tools that help writing. Such tools can proofread the text and find spelling mistakes or stylistic problems. The style and spell checker could also verify that the text follows the set rules of a controlled language.