Natural Language Processing and AI

Natural Language Processing (NPL) is playing an important role in Artificial Intelligence.

Natural Language Processing widely known as NLP is a part of machine learning. NLP has the potential to recognize, analyze, exploit and produce human language. Due to its capability, it’s extremely useful for computers to analyze the text and detect spam emails, autocorrect, etc. Basically, you can say it’s a junction of Artificial Intelligence, Computer Science, and Computer Linguistics. As we know computer systems understand only the language of 0 and 1. It is not capable of understanding human languages like English, French or Spanish, etc. but natural language processing has made it able for the computer to understand those languages. Due to which it is extremely beneficial for AI startups to use it in their products.

Machine Learning and its role in Natural Language Processing

Machine Learning plays an important role by helping in the processing of natural language for the system to understand and execute accordingly. Let's take a look at the number of tasks that are involved in it,

1. Morphological Analysis:

Here the data which is received is divided into two groups tokenization and stemming. As we know the computer system only understands 0 and 1. The tokenization identifies the word and sentences with the help of algorithms like SVM, and Recurrent Neural Network. To make it easier for the system to understand all the affixes which are used in sentences are removed by stemming with the help of algorithms like random forest and decision trees.

2. Syntactic Analysis:

Syntactic Analysis is used in checking the grammar rules. For this algorithms like the random forest and the recurrent neural network is used.

3. Semantic Analysis:

Semantic Analysis is used in differentiating the meaning of the same word according to the sentence. Here in NLP, it is called word sense Disambiguation.

4. Discourse Analysis:

Discourse Analyses are used in dealing with the pronouns that are used for subjects and objects.

5. Pragmatic Analysis:

Pragmatic Analysis helps in understanding the deeper meaning of the sentences and words.

Natural Language Processing and its Application

• Information Recovery
• Information withdrawal
• Spam Filter
• Auto-predict and Auto-correct
• Speech Recognition.
• Natural language generation
• Question and answering

Hence we can say that machine learning and deep learning are been extremely helpful for Natural language Processing and its Applications.