Morphological analysis is a foundational NLP technique that segments text into morphemes (the smallest meaningful units) and assigns grammatical information such as part of speech, reading, and base form. It is especially critical for languages like Japanese that lack spaces between words.

Popular morphological analyzers include MeCab, kuromoji (Java), and Sudachi. Analyzing "東京都に住んでいる" produces segments like "東京/都/に/住ん/で/いる." NLP introduction books explain how morphological analysis works.

It is used in search engine indexing, word counting in text tools, sentiment analysis preprocessing, and many other applications.

English can be tokenized by spaces, reducing the need for morphological analysis. However, for CJK languages (Chinese, Japanese, Korean), it is an indispensable technique. Morphological analysis NLP books cover practical implementation.