Scaling laws in human speech, decreasing emergence of new words and a generalized model
This addresses the problem of understanding language evolution for researchers in physics and culture, but it is incremental as it extends known laws to speech with new data.
The paper analyzed the organization of human speech, finding that it follows Zipf's and Heaps' laws like written text, but with word frequencies more concentrated on common words and a faster decrease in new word emergence as length increases. It proposed a generalized model to explain these dynamics and differences from books.
Human language, as a typical complex system, its organization and evolution is an attractive topic for both physical and cultural researchers. In this paper, we present the first exhaustive analysis of the text organization of human speech. Two important results are that: (i) the construction and organization of spoken language can be characterized as Zipf's law and Heaps' law, as observed in written texts; (ii) word frequency vs. rank distribution and the growth of distinct words with the increase of text length shows significant differences between book and speech. In speech word frequency distribution are more concentrated on higher frequency words, and the emergence of new words decreases much rapidly when the content length grows. Based on these observations, a new generalized model is proposed to explain these complex dynamical behaviors and the differences between speech and book.