Types Of Natural Language Processing
Syntax Analysis (Parsing)
Analyzes sentence structure and grammar to identify relationships between words, enabling machines to understand text syntax accurately.
Semantic Analysis
Extracts meaning from text by interpreting context and relationships between words to comprehend the underlying message effectively.
Sentiment Analysis
Detects emotions and opinions in text by classifying sentiment polarity such as positive, negative, or neutral feelings expressed.
Named Entity Recognition (NER)
Identifies and classifies key entities like people, places, dates, and organizations within text for structured information extraction.
Speech Recognition
Converts spoken language into written text by analyzing audio signals, enabling voice-controlled applications and transcription services.
Text Summarization
Generates concise and coherent summaries of long texts by extracting key points while preserving the original meaning and context.
Text Classification
Categorizes text documents into predefined classes or topics by analyzing content features for organization and retrieval tasks.
Machine Translation
Automatically translates text between languages by understanding context, grammar, and semantics to produce accurate multilingual outputs.