Natural language processing (NLP)
It is the ability of a computer program to understand human language as it is spoken. NLP is a component of artificial intelligence.
The development of NLP applications is challenging because computers traditionally require humans to “speak” to them in a programming language that is precise, unambiguous and highly structured, or through a limited number of clearly enunciated voice commands.
Current approaches to NLP are based on deep learning, a type of AI that examines and uses patterns in data to improve a program’s understanding. Deep learning models require massive amounts of labeled data to train on and identify relevant correlations, and assembling this kind of big data set is one of the main hurdles to NLP currently.
Benefits of NLP
- Improved accuracy and efficiency of documentation.
- The ability to automatically make a readable summary text.
- Useful for personal assistants such as Alexa.
- Allows an organization to use chatbots for customer support.
- Easier to perform sentiment analysis
Challenges associated with NLP
NLP has not yet been wholly perfected. For example, semantic analysis can still be a challenge for NLP. Other difficulties include the fact that abstract use of language is typically tricky for programs to understand. For instance, NLP does not pick up sarcasm easily. These topics usually require the understanding of the words being used and the context in which the way they are being used. As another example, a sentence can change meaning depending on which word the speaker puts stress on. NLP is also challenged by the fact that language, and the way people use it, is continually changing.