Abstract

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.

Highlights

  • We propose the first statistical theory of language translation based on communication theory

  • 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

  • We propose to use this formula for the other languages listed in Table 1, by scaling the constant 10 of the semantic term according to the ratio between the average number of characters per word in Italian, Cp,ITA = 4.48, and the average number of characters per word in another language, e.g., Greek Cp,GRE = 4.86, see Table 1

Read more

Summary

A Statistical Theory of Language Translation Based on Communication Theory

Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milan, Italy.

A Communication Channel Approach to the Theory of Translation
Matricciani DOI
Translations
The Ideal Translation and the Real Translation
Noise-to-Signal Power Ratio and Its Universal Geometrical Representation
Linguistic Communication Channels
Channel Capacity
Channel Capacity According to Communication Theory
Channel Capacity Size
Word Interval and Short-Term Memory
Readability Index
Different NT Translations within the Same Language
10. Literary Text Translations
11. A General Theory of Translation
11.1. Noise-to-Signal Power Ratio
11.2. Direct and Reverse Channels Are Not Symmetric
11.3. Direct and Reverse Channels Capacity Difference
Findings
12. Conclusions
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call