Zipf's Law is a statistical principle stating that a small number of words occur very frequently while most words appear rarely in natural language. This distribution influences language modeling and vocabulary design.
Voice AI researchers use Zipf's Law when developing speech recognition systems, language models, tokenization strategies, and vocabulary optimization techniques.