Natural Language Understanding (NLU)

NLU (Natural Language Understanding)

Definition

Natural Language Understanding (NLU) is a subfield of NLP that focuses on interpreting the meaning, intent, and context of human language.

Purpose

The purpose is to allow AI to comprehend human inputs beyond surface-level text. It enables intent recognition, question answering, and semantic analysis.

Importance

  • Critical for conversational AI.
  • Enables context-aware systems.
  • Errors reduce user satisfaction and trust.
  • Requires robust handling of ambiguity in language.

How It Works

  1. Tokenize and preprocess input text.
  2. Apply models to detect intent and extract entities.
  3. Represent meaning with embeddings or semantic graphs.
  4. Map results to system actions or responses.
  5. Continuously refine through feedback.

Examples (Real World)

  • Siri: interprets spoken queries and commands.
  • Google Assistant: maps language to actions.
  • IBM Watson: NLU applied in healthcare and customer service.

References / Further Reading

  • Allen. Natural Language Understanding. Benjamin Cummings.
  • Jurafsky & Martin. Speech and Language Processing.
  • IEEE Intelligent Systems — NLP and NLU Research.