In philology, decipherment is the discovery of the meaning of the symbols found in extinct languages and/or alphabets. Decipherment overlaps with another technical field known as cryptanalysis, a field that aims to decipher writings used in secret communication, known as ciphertext. A famous case of this was in the cryptanalysis of the Enigma during the World War II. Many other ciphers from past wars have only recently been cracked. Unlike in language decipherment, however, actors using ciphertext intentionally lay obstacles to prevent outsiders from uncovering the meaning of the communication system. Today, at least a dozen languages remain undeciphered. A notable recent decipherment was that of the Linear Elamite script.

Categories

According to Gelb and Whiting, the approach of decipherment depends on four categories of situations in an undeciphered language:

Methods

A number of methods are available to go about deciphering an extinct writing system or language. These can be divided into approaches utilizing external or internal information.

External information

Many successful encipherments have proceeded from the discovery of external information, a common example being through the use of multilingual inscriptions, such as the Rosetta Stone (with the same text in three scripts: Demotic, hieroglyphic, and Greek) that enabled the decipherment of Egyptian hieroglyphic. In principle, multilingual text may be insufficient for a decipherment as translation is not a linear and reversible process, but instead represents an encoding of the message in a different symbolic system. Translating a text from one language into a second, and then from the second language back into the first, rarely reproduces exactly the original writing. Likewise, unless a significant number of words are contained in the multilingual text, limited information can be gleaned from it.

Internal information

Internal approaches are multi-step: one must first ensure that the writing they are looking at represents real writing, as opposed to a grouping of pictorial representations or a modern-day forgery without further meaning. This is commonly approached with methods from the field of grammatology. Prior to decipherment of meaning, one can then determine the number of distinct graphemes (which, in turn, allows one to tell if the writing system is alphabetic, syllabic, or logo-syllabic; this is because such writing systems typically do not overlap in the number of graphemes they use ), the sequence of writing (whether it be from left to right, right to left, top to bottom, etc.), and the determination of whether individual words are properly segmented when the alphabet is written (such as with the use of a space or a different special mark) or not. If a repetitive schematic arrangement can be identified, this can help in decipherment. For example, if the last line of a text has a small number, it can be reasonably guessed to be referring to the date, where one of the words means "year" and, sometimes, a royal name also appears. Another case is when the text contains many small numbers, followed by a word, followed by a larger number; here, the word likely means "total" or "sum". After one has exhausted the information that can be inferentially derived from probable content, they must transition to the systematic application of statistical tools. These include methods concerning the frequency of appearance of each symbol, the order in which these symbols typically appear, whether some symbols appear at the beginning or end of words, etc. There are situations where orthographic features of a language make it difficult if not impossible to decipher specific features (especially without certain outside information), such as when an alphabet does not express double consonants. Additional, and more complex methods, also exist. Eventually, the application of such statistical methods becomes exceedingly laborious, in which computers might be used to apply them automatically.

Computational approaches

Computational approaches towards the decipherment of unknown languages began to appear in the late 1990s. Typically, there are two types of computational approaches used in language decipherment: approaches meant to produce translations in known languages, and approaches used to detect new information that might enable future efforts at translation. The second approach is more common, and includes things such as the detection of cognates or related words, discovery of the closest known language, word alignments, and more.

Artificial intelligence

In recent years, there has been a growing emphasis on methods utilizing artificial intelligence for the decipherment of lost languages, especially through natural language processing (NLP) methods. Proof-of-concept methods have independently re-deciphered Ugaritic and Linear B using data from similar languages, in this case Hebrew and Ancient Greek.

Deciphering pronunciation

Related to attempts to decipher the meaning of languages and alphabets, include attempts to decipher how extinct writing systems, or older versions of contemporary writing systems (such as English in the 1600s) were pronounced. Several methods and criteria have been developed in this regard. Important criteria include (1) Rhymes and the testimony of poetry (2) Evidence from occasional spellings and misspellings (3) Interpretations of material in one language from authors in foreign languags (4) Information obtained from related languages (5) Grammatical changes in spelling over time. For example, analysis of poetry focuses on the use of wordplay or literary techniques between words that have a similar sound. Shakespeare's play Romeo and Juliet contains wordplay that relies on a similar sound between the words "soul" and "soles", allowing confidence that the similar pronunciation between the terms today also existed in Shakespeare's time. Another common source of information on pronunciation is when earlier texts use rhyme, such as when consecutive lines in poetry end in the similar or the same sound. This method does have some limitations however, as texts may use rhymes that rely on visual similarities between words (such as 'love' and 'remove') as opposed to auditory similarities, and that rhymes can be imperfect. Another source of information about pronunciation comes from explicit description of pronunciations from earlier texts, as in the case of the Grammatica Anglicana, such as in the following comment about the letter <o>: "In the long time it naturally soundeth sharp, and high; as in chósen, hósen, hóly, fólly [. . .] In the short time more flat, and a kin to u; as còsen, dòsen, mòther, bròther, lòve, pròve". Another example comes from detailed comments on pronunciations of Sanskrit from the surviving works of Sanskrit grammarians.

Challenges

Many challenges exist in the decipherment of languages, including when:

Notable decipherers

Deciphered scripts

Undeciphered scripts

Undeciphered texts