Text normalization converts text into standard or canonical form. It ensures consistency and helps in processing and analysis. There is no single approach to the normalization process. The first step in normalization is the lower case all the text. It is the simplest, most applicable, and effective method for text pre-processing. Another approach could be handling wrongly spelled words, acronyms, short forms, and the use of out-of-vocabulary words; for example, "super," "superb," and "superrrr" can be converted into "super". Text normalization handles the noise and disturbance in test data and prepares noise-free data. We also apply stemming and lemmatization to normalize the words present in the text.
Let's perform a basic normalization operation by converting the text into lowercase:
# Input text
paragraph="""Taj Mahal is one of the beautiful monuments. It is one of the wonders of the world. It was built...
