Natural language processing in artificial intelligence
- 1. Natural Language Processing in Artificial Intelligence
- 2. Natural Language Processing(NLP) Natural Language Processing, usually shortened as NLP, is a branch of artificial intelligence that deals with the interaction between computers and humans using the natural language. The ultimate objective of NLP is to read, understand and make sense of the human languages in a manner that is valuable. 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
- 3. Process Flow: Simply an interaction between humans and machines using Natural Language Processing could go as follows: 1. A human talks to the machine 2. The machine captures the audio 3. Audio to text conversion takes place 4. Processing of the text’s data 5. Data to audio conversion takes place 6. The machine responds to the human by playing the audio file
- 4. Where we use NLP? Language translation applications such as Google Translate Word Processors such as Microsoft Word that employ NLP to check grammatical accuracy of texts. Interactive Voice Response (IVR) applications used in call centers to respond to certain users’ requests. Personal assistant applications such as OK Google, Siri, Cortana, and Alexa.
- 5. How does Natural Language Processing Works? NLP entails applying algorithms to identify and extract the natural language rules such that the unstructured language data is converted into a form that computers can understand. When the text has been provided, the computer will utilize algorithms to extract meaning associated with every sentence and collect the essential data from them. Sometimes, the computer may fail to understand the meaning of a sentence well, leading to obscure results due to the pronunciation and other human problems.
- 6. Techniques used in NLP Syntactic analysis and semantic analysis are the main techniques used to complete Natural Language Processing tasks. Syntax: Syntax refers to the arrangement of words in a sentence such that they make grammatical sense. In NLP, syntactic analysis is used to assess how the natural language aligns with the grammatical rules. Computer algorithms are used to apply grammatical rules to a group of words and derive meaning from them. Semantics: Semantics refers to the meaning that is conveyed by a text. Semantic analysis is one of the difficult aspects of Natural Language Processing that has not been fully resolved yet. It involves applying computer algorithms to understand the meaning and interpretation of words and how sentences are structured.
- 7. Conclusion: Natural Language Processing plays a critical role in supporting machine-human interactions. As more research is being carried in this field, we expect to see more breakthroughs that will make machines smarter at recognizing and understanding the human language. Software like Google assistant, Siri, Cortana and more are making life easy of humans and help them to interact with computer more and more.