Measuring Language Distance of Isolated European Languages

Gamallo, Pablo; Campos, José Ramom Pichel; Alegria, Iñaki

doi:10.3390/info11040181

Cited by 8 publications

(4 citation statements)

References 31 publications

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“…For example, References [4][5][6][7][8] report results not based on mathematical analysis of texts, as we do. When a mathematical approach is used, as in References [9][10][11][12][13][14][15][16][17][18][19], most of these studies neither concern the aspects of Shannon's Communication Theory [20], nor the fundamental connection which some linguistic variables have with reader's reading ability and short-term memory capacity, considered instead in [1,2]. In fact, these studies are mainly concerned with machine translations, not with human response.…”

Section: Machine Translation and Its Vast Literaturementioning

confidence: 99%

Linguistic Mathematical Relationships Saved or Lost in Translating Texts: Extension of the Statistical Theory of Translation and Its Application to the New Testament

Matricciani

2022

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The purpose of the paper is to extend the general theory of translation to texts written in the same language and show some possible applications. The main result shows that the mutual mathematical relationships of texts in a language have been saved or lost in translating them into another language and consequently texts have been mathematically distorted. To make objective comparisons, we have defined a “likeness index”—based on probability and communication theory of noisy binary digital channels-and have shown that it can reveal similarities and differences of texts. We have applied the extended theory to the New Testament translations and have assessed how much the mutual mathematical relationships present in the original Greek texts have been saved or lost in 36 languages. To avoid the inaccuracy, due to the small sample size from which the input data (regression lines) are calculated, we have adopted a “renormalization” based on Monte Carlo simulations whose results we consider as “experimental”. In general, we have found that in many languages/translations the original linguistic relationships have been lost and texts mathematically distorted. The theory can be applied to texts translated by machines. Because the theory deals with linear regression lines, the concepts of signal-to-noise-ratio and likenss index can be applied any time a scientific/technical problem involves two or more linear regression lines, therefore it is not limited to linguistic variables but it is universal.

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Section: Machine Translation and Its Vast Literaturementioning

confidence: 99%

Linguistic Mathematical Relationships Saved or Lost in Translating Texts: Extension of the Statistical Theory of Translation and Its Application to the New Testament

Matricciani

2022

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“…References [6]- [12] report results not based on mathematical analysis of texts, as we have done [1] [2] [3]. When a mathematical approach is used, as in References [13]- [25], most of these studies neither concern the aspects of Shannon's communication theory [26], nor the fundamental connection that some linguistic variables have with reader's reading ability and short-term memory capacity [1] [2] [3]. In fact, these studies are mainly concerned with automatic translations, not with a response of human readers.…”

Section: Textsmentioning

confidence: 99%

Multiple Communication Channels in Literary Texts

Matricciani¹

2022

OJS

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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 L I , 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 0.5 L I ≈ , 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.

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“…References [3]- [9] report results not based on mathematical analysis of texts, as we do with the theory here proposed. When a mathematical approach is used, as in References [10]- [25], most of these studies neither concern the aspects of Shannon's communication theory [26], nor the fundamental connection which some linguistic variables have with reader's reading ability and short-term memory capacity, considered instead in this paper. In fact, these studies are mainly concerned with machine translations, not with a response of human readers.…”

Section: A Communication Channel Approach To the Theory Of Translationmentioning

confidence: 99%

A Statistical Theory of Language Translation Based on Communication Theory

Matricciani¹

2020

OJS

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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. How to cite this paper: Matricciani, E.

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Measuring Language Distance of Isolated European Languages

Cited by 8 publications

References 31 publications

Linguistic Mathematical Relationships Saved or Lost in Translating Texts: Extension of the Statistical Theory of Translation and Its Application to the New Testament

Linguistic Mathematical Relationships Saved or Lost in Translating Texts: Extension of the Statistical Theory of Translation and Its Application to the New Testament

Multiple Communication Channels in Literary Texts

A Statistical Theory of Language Translation Based on Communication Theory

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