NATURAL LANGUAGE PROCESSING - NLP is a field of Artifical Intelligence, Computer Science, and linguistics

 

NATURAL LANGUAGE PROCESSING - NLP is a field of Artifical Intelligence, Computer Science, and linguistics

Natural Language Processing is a field of Artifical Intelligence, Computer Science, and linguistics that focuses on enabling computers to understand, interpret, and generate human language.

It’s a bridge between human communication and machine understanding, allowing computers to process and make sense of text and speech.

Natural Language processing (NLP) is the ability of computer program to understand human language as it’s spoken and written referred to as natural language.

5 steps in NLP:

1.      Lexical or Morphological Analysis: This initial phase focuses on breaking down the input text into smaller units like paragraphs, sentences, and words. It also involves identifying the grammatical category of each word (e.g., noun, verb, adjective).

2.      Syntactic Analysis (Parsing): Syntactic Analysis examines the grammatical structure of sentences, determining how words are arranged and how they relate to each other. It identifies elements like subject, verb, object and other grammatical components to understand the sentence’s structure.

3.      Semantic Analysis: This phase goes beyond the grammatical structure to understand the literal meaning of words and sentences. It focuses on the meaning of individual words, phrases, and how they combine to create overall meaning within the sentence.

4.      Discourse Integration: Discourse Integration analyzes how sentences connect and relate to each other within a larger text or conversation.

5.      Pragmatic Analysis: The final phase deals with understanding the intended meaning of an utterance in context. This involves considering factors like the speaker’s intent, the situation, and   cultural context to interpret the meaning beyond the literal words and sentences.

How it works:

1.Data Processing: Raw text or speech is cleaned and prepared for processing algorithms.

2.Language Modeling: Algorithms, often using machine learning, learn patterns and structures in language to understand the generate text or speech.

3.Task-Specific Processing: NLP is applied to various tasks like sentiment analysis, machine translation, question answering, and more.

Core Concepts:

1.Understanding Language: NLP algorithms analyze text and speech to extract meaning, identify sentiment, and understand the intent behind communication.

2.Language Generation: NLP can also generate human- like text, such as in chat bots, language translation, and content creation.

3.Interdisciplinary Field: NLP combines computational linguistics (modeling language structure) with machine learning and deep learning techniques.

Applications of NLP:

Ø  Chat bots and Virtual Assistants: NLP powers conversational interface that understand and respond to user input.

Ø  Machine Translation: NLP enables accurate translation between languages.

Ø   Sentiment Analysis: NLP identifies and categorizes opinions and emotions expressed in text.

Ø  Text Summarization: NLP condenses large amount of text into shorter, concise summaries.

Ø  Information Retrieval: NLP helps search engines understand user queries and provide relevant results.

Ø  Spam Filtering: NLP identifies and filters out unwanted email messages.

Advantages of NLP:

1.Large –scale analysis.

2.Get a more impartial, precise analysis.

3.Improve client satisfaction.

4.Understand your market.

5.Give workers power.

6. Actual, actionable insights.

7.Voice assistants.

8.Intuitive communication.

9.Automated tasks.

10.Improved productivity.

11.Reduced costs.

12.Language Translation.

13.Speech-to-text.

14.Fraud detection.

15. Health care Applications.

16.Information Extractions.