TITLE:
Short-Term Memory Capacity across Time and Language Estimated from Ancient and Modern Literary Texts. Study-Case: New Testament Translations
AUTHORS:
Emilio Matricciani
KEYWORDS:
Alphabetical Languages, Artificial Intelligence Writing, Greek, Latin, New Testament, Readers Overlap Probability, Short-Term Memory Capacity, Texts, Translation, Words Interval
JOURNAL NAME:
Open Journal of Statistics,
Vol.13 No.3,
June
27,
2023
ABSTRACT: We study
the short-term memory capacity of ancient readers of the original New Testament
written in Greek, of its translations to Latin and to modern languages. To
model it, we consider the number of words between any two contiguous
interpunctions Ip, because
this parameter can model how the human mind memorizes “chunks” of information.
Since IP can be calculated
for any alphabetical text, we can perform experiments—otherwise impossible— with
ancient readers by studying the literary works they used to read. The
“experiments” compare the IP of texts of a language/translation to those of another language/translation by
measuring the minimum average probability of finding joint readers (those who
can read both texts because of similar short-term memory capacity) and by defining an “overlap
index”. We also define the population of universal readers, people who can
read any New Testament text in any language. Future work is vast, with many
research tracks, because alphabetical literatures are very large and allow many
experiments, such as comparing authors, translations or even texts written by
artificial intelligence tools.