Natural Language Understanding (NLU)

Natural Language Understanding (NLU) is a subset of NLP focused on enabling machines to comprehend the intent and meaning behind text or speech. It involves tasks like sentiment analysis, entity recognition, and intent classification.

Also known as: Semantic processing.

Comparisons

• NLU vs. NLG: NLU focuses on understanding input language, while NLG focuses on generating output language.

• NLU vs. Speech Recognition: NLU interprets meaning, whereas speech recognition transcribes spoken language into text.

Pros

• Better context handling: Understands the user’s intent beyond individual words.

• Improves user experience: Enables intelligent virtual assistants and search engines.

• Versatile: Supports multiple languages and applications.

Cons

• Challenges with nuance: Struggles with humor, sarcasm, or ambiguous language.

• High computational needs: Requires robust processing capabilities.

Example

An email filtering system uses NLU to categorize emails as spam, promotional, or important based on the content’s meaning and intent.