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...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 I<sub>p</sub>, because this parameter can model how the human mind memorizes “chunks” of information. Since I<sub>P</sub> 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 I<sub>P</sub> 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.展开更多
The statistical theory of language translation is used to compare how a literary character speaks to different audiences by diversifying two important linguistic communication channels: the “sentences channel” and t...The statistical theory of language translation is used to compare how a literary character speaks to different audiences by diversifying two important linguistic communication channels: the “sentences channel” and the “interpunctions channel”. The theory can “measure” how the author shapes a character speaking to different audiences, by modulating deep-language parameters. To show its power, we have applied the theory to the literary corpus of Maria Valtorta, an Italian mystic of the XX-century. The likeness index , ranging from 0 to 1, allows to “measure” how two linguistic channels are similar, therefore implying that a character speaks to different audiences in the same way. A 6-dB difference between the signal-to-noise ratios of two channels already gives I<sub>L</sub> ≈ 0.5, a threshold below which the two channels depend very little on each other, therefore implying that the character addresses different audiences differently. In conclusion, multiple linguistic channels can describe the “fine tuning” that a literary author uses to diversify characters or distinguish the behavior of the same character in different situations. The theory can be applied to literary corpora written in any alphabetical language.展开更多
A multi-dimensional mathematical theory applied to texts belonging to the classical Greek Literature spanning eight centuries reveals interesting connections between them. By studying words, sentences, and interpuncti...A multi-dimensional mathematical theory applied to texts belonging to the classical Greek Literature spanning eight centuries reveals interesting connections between them. By studying words, sentences, and interpunctions in texts, the theory defines deep-language variables and linguistic channels. These mathematical entities are due to writer’s unconscious design and can reveal connections between texts far beyond writer’s awareness. The analysis, based on 3,225,839 words contained in 118,952 sentences, shows that ancient Greek writers, and their readers, were not significantly different from modern writers/readers. Their sentences were processed by a short-term memory modelled with two independent processing units in series, just like modern readers do. In a society in which people were used to memorize information more often than modern people do, the ancient writers wrote almost exactly, mathematically speaking, as modern writers do and for readers of similar characteristics. Since meaning is not considered by the theory, any text of any alphabetical language can be studied exactly with the same mathematical/statistical tools and comparisons are possible, regardless of different languages and epochs of writing.展开更多
文摘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 I<sub>p</sub>, because this parameter can model how the human mind memorizes “chunks” of information. Since I<sub>P</sub> 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 I<sub>P</sub> 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.
文摘The statistical theory of language translation is used to compare how a literary character speaks to different audiences by diversifying two important linguistic communication channels: the “sentences channel” and the “interpunctions channel”. The theory can “measure” how the author shapes a character speaking to different audiences, by modulating deep-language parameters. To show its power, we have applied the theory to the literary corpus of Maria Valtorta, an Italian mystic of the XX-century. The likeness index , ranging from 0 to 1, allows to “measure” how two linguistic channels are similar, therefore implying that a character speaks to different audiences in the same way. A 6-dB difference between the signal-to-noise ratios of two channels already gives I<sub>L</sub> ≈ 0.5, a threshold below which the two channels depend very little on each other, therefore implying that the character addresses different audiences differently. In conclusion, multiple linguistic channels can describe the “fine tuning” that a literary author uses to diversify characters or distinguish the behavior of the same character in different situations. The theory can be applied to literary corpora written in any alphabetical language.
文摘A multi-dimensional mathematical theory applied to texts belonging to the classical Greek Literature spanning eight centuries reveals interesting connections between them. By studying words, sentences, and interpunctions in texts, the theory defines deep-language variables and linguistic channels. These mathematical entities are due to writer’s unconscious design and can reveal connections between texts far beyond writer’s awareness. The analysis, based on 3,225,839 words contained in 118,952 sentences, shows that ancient Greek writers, and their readers, were not significantly different from modern writers/readers. Their sentences were processed by a short-term memory modelled with two independent processing units in series, just like modern readers do. In a society in which people were used to memorize information more often than modern people do, the ancient writers wrote almost exactly, mathematically speaking, as modern writers do and for readers of similar characteristics. Since meaning is not considered by the theory, any text of any alphabetical language can be studied exactly with the same mathematical/statistical tools and comparisons are possible, regardless of different languages and epochs of writing.
