Short-Term Memory Capacity across Time and Language Estimated from Ancient and Modern Literary Texts. Study-Case: New Testament Translations

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.

Deep Language Statistics of Italian throughout Seven Centuries of Literature and Empirical Connections with Miller’s 7 ∓2 Law and Short-Term Memory

Statistics of languages are usually calculated by counting characters, words, sentences, word rankings. Some of these random variables are also the main “ingredients” of classical readability formulae. Revisiting the readability formula of Italian, known as GULPEASE, shows that of the two terms that determine the readability index G—the semantic index , proportional to the number of characters per word, and the syntactic index GF, proportional to the reciprocal of the number of words per sentence—GF is dominant because GC is, in practice, constant for any author throughout seven centuries of Italian Literature. Each author can modulate the length of sentences more freely than he can do with the length of words, and in different ways from author to author. For any author, any couple of text variables can be modelled by a linear relationship y = mx, but with different slope m from author to author, except for the relationship between characters and words, which is unique for all. The most important relationship found in the paper is that between the short-term memory capacity, described by Miller’s “7 ? 2 law” (i.e., the number of “chunks” that an average person can hold in the short-term memory ranges from 5 to 9), and the word interval, a new random variable defined as the average number of words between two successive punctuation marks. The word interval can be converted into a time interval through the average reading speed. The word interval spreads in the same range as Miller’s law, and the time interval is spread in the same range of short-term memory response times. The connection between the word interval (and time interval) and short-term memory appears, at least empirically, justified and natural, however, to be further investigated. Technical and scientific writings (papers, essays, etc.) ask more to their readers because words are on the average longer, the readability index G is lower, word and time intervals are longer. Future work done on ancient languages, such as the classical Greek and Latin Literatures (or modern languages Literatures), could bring us an insight into the short-term memory required to their well-educated ancient readers.

A Statistical Theory of Language Translation Based on Communication Theory

We propose the first statistical theory of language translation based on communication theory. The theory is based on New Testament translations from Greek to Latin and to other 35 modern languages. In a text translated into another language, all linguistic variables do numerically change. To study the chaotic data that emerge, we model any translation as a complex communication channel affected by “noise”, studied according to Communication Theory applied for the first time to this channel. This theory deals with aspects of languages more complex than those currently considered in machine translations. The input language is the “signal”, the output language is a “replica” of the input language, but largely perturbed by noise, indispensable, however, for conveying the meaning of the input language to its readers. We have defined a noise-to-signal power ratio and found that channels are differently affected by translation noise. Communication channels are also characterized by channel capacity. The translation of novels has more constraints than the New Testament translations. We propose a global readability formula for alphabetical languages, not available for most of them, and conclude with a general theory of language translation which shows that direct and reverse channels are not symmetric. The general theory can also be applied to channels of texts belonging to the same language both to study how texts of the same author may have changed over time, or to compare texts of different authors. In conclusion, a common underlying mathematical structure governing human textual/verbal communication channels seems to emerge. Language does not play the only role in translation;this role is shared with reader’s reading ability and short-term memory capacity. Different versions of New Testament within the same language can even seem, mathematically, to belong to different languages. These conclusions are everlasting because valid also for ancient Roman and Greek readers.

The Temporal Making of a Great Literary Corpus by a XX-Century Mystic: Statistics of Daily Words and Writing Time

Maria Valtorta (1897-1961, Italian mystic)—bedridden since 1934 because paralyzed—wrote in Italian 13,193 pages of 122 school notebooks concerning alleged mystical visions on Jesus’ life, during World War II and few following years. The contents—about 2.64 million words—are now scattered in different books. She could write from 2 to 6 hours without pausing, with steady speed, and twice in the same day. She never made corrections and was very proficient in Italian. We have studied her writing activity concerning her alleged mystical experience with the main scope of establishing the time sequence of daily writing. This is possible because she diligently annotated the date of almost every text. We have reconstructed the time series of daily words and have converted them into time series of writing time, by assuming a realistic speed of 20 words per minute, a reliable average value of fast handwriting speed, applicable to Maria Valtorta. She wrote for 1340 days, about 3.67 years of equivalent contiguous writing time, mostly concentrated in the years 1943 to 1948. This study is a first approach in evaluating the effort done, in terms of writing time, by a mystic turned out to be a very effective literary author, whose texts are interesting to read per se, beyond any judgement—not of concern here—on her alleged visions.

Multiple Communication Channels in Literary Texts

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 IL ≈ 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.