摘要：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.
