The domain of research that point out the interactions between human languages and computers is called Natural Language Processing or NLP. It stands at the junction of computer science, artificial intelligence and computational linguistics.
NLP is a path for computers to inspect, understand and derive meaning from human language in a smart and useful manner. Through NLP, developers of it can collect and establish ideas to perform tasks such as automatic summarization, translation, entity recognition, sentiment/emotion analysis and speech recognition. It also has advanced features like correcting grammar, converting speech to text and automatically translates between two languages. NLP is generally used for text mining, machine translation and automated question answering.
A 2017 report on the natural language processing (NLP) market estimated that the total NLP software, hardware and services market share to be around $22.3 billion by 2025. The report also says that NLP software solutions influencing Artificial Intelligence will see a market growth from $136 million in 2016 to $5.4 billion by 2025.
We can see in the below mentioned figure
Example Natural Language Processing Use Cases
NLP is based on machine learning algorithms. Rather than using hand coding commands, NLP can rely on machine learning to automatically learn these set of rules by interpreting a set of examples. Social media analysis is an example of NLP use.
Current Applications of Natural Language Processing
Some of the current virtual assistance solutions using NLP serve as intelligence enhancement. In such applications, a customer’s first request is checked by the artificial intelligence such as apps like Nina. E.g. a banking customer service system uses the AI to answer some basic transactional difficulties such as opening an account or to figure out the best loyal customer of the bank.
It also offers automotive virtual assistants connected to flagship cars OEM like BMW, JAGUAR, AUDI and others. One press release on Nuance’s partnership with BMW mentioned about Dragon Drive AI which enables drivers to access apps and services through voice commands, navigation, music, message, calendar, weather and social media.
It is possible to give a command to Artificial Intelligence to send a text message right from the car like, text Bella, “I will reach 10 minutes late at home” or “Get me directions to Dominos Pizza in Indore” etc.
NLP also provides solutions in healthcare domain. It includes clinical document improvement solutions. CDI is a process of improvising healthcare record of the patients to ensure good health of a patient, data quality etc. In this field AI allows physicians to write progress notes of patients, history of present illness and also plans or strategies need to be adopted for further actions. NLP provides real-time intelligence to physicians by automatically prompting them with clarifying questions while they are documenting.
There are many AI & NLP applications in the market. It is very important to choose the correct application that can resolve business problems with the help of technology and provide value.
Finally, businesses must have enough relevant data for learning algorithms for accurate outputs.
Future possibilities with NLP
- Researchers are working on making AI more human-like, which is really a tough task. (E.g. making a conversational AI)
- Expansion of existing AI technologies (E.g. extending automatic picture captioning to healthcare and other applications for clarification of image)