Abstract

In the present article, we have further developed the model on the input-output equivalent characteristics of the short-term memory—evaluated form alphabetical texts—by including a processor that memorizes syllables to produce a word. The final model is made of three equivalent processors in series, which independently process: (1) syllables to make a word; (2) words to make a word interval; (3) word intervals to make a sentence. This is a simple but useful approach because the multiple processing of the brain regarding speech/texts is not yet fully understood but syllables, characters, words can be studied in any alphabetical language. We have considered modern translations of the New Testament because these texts address general audiences accustomed to reading common words, not specialized literature. The deep-language parameters—linked to syllables, characters, words and interpunctions—of indistinct human readers/writers are specifically defined with probability distribution functions that provide useful ranges on the communication digital codes that humans can further invent. Their application to a universal readability formula can provide also an estimate of the distribution of readers and texts that these readers can read with a given “built-in” difficulty, as a function of their schooling. Finally, the theory can inspire new research lines in cognitive science studies.

Keywords: Balto-Slavic languages, Language processing, Deep-language, Germanic languages, Greek, Latin, New testament, Romance languages, Short-termmemory, Translation, Uralic languages