Text normalization is a common NLP preprocessing step that converts raw text into a consistent, “clean” form so downstream models see fewer superficial variations. In this task, you’ll implement a simple normalizer with a few standard rules.

Requirements

Implement the function

Rules:

• For each string, lowercase it.
• Remove punctuation characters: .,!?;:\'"()-
• Replace any sequence of whitespace (spaces, tabs, newlines) with a single space.
• Trim leading and trailing spaces.
• Report the normalization rate as: $$r = \frac{\text{total removed characters}}{\text{total original characters}}$$ and return it along with the normalized texts as (normalized_texts, r).

Example

Output: