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recognized. In addition, IPA may be used for pronunciation, Greek letters may be used for
classical Greek quotations, and Greek letters and other special characters may be used for
<strong>in</strong>dicat<strong>in</strong>g footnotes or other references (Breuel 2009).
The challenge of multil<strong>in</strong>gual document recognition is a significant one for classical scholarship that
has been reported by many digital classics projects. OCRopus has built-<strong>in</strong> l<strong>in</strong>e recognizers for Lat<strong>in</strong>
scripts, and unlike those of many other OCR systems, these recognizers make few assumptions about
character sets and fonts and are <strong>in</strong>stead “tra<strong>in</strong>ed” on text-l<strong>in</strong>e <strong>in</strong>put that is then aligned aga<strong>in</strong>st ground
truth data and can be used to automatically tra<strong>in</strong> “<strong>in</strong>dividual character shape models.” For Devanagari,
OCRopus handled diacritics by treat<strong>in</strong>g “character+diacritic” comb<strong>in</strong>ations as novel characters.
The f<strong>in</strong>al process<strong>in</strong>g stage of OCRopus is language model<strong>in</strong>g, which <strong>in</strong> the case of OCRopus is based
on WFSTs. WFSTs allow language models and character recognition alternatives to be “manipulated
algebraically” and such language models can be learned from tra<strong>in</strong><strong>in</strong>g data or constructed manually.
One important use of such models for mixed-language classical texts is that they can be used to
automatically identify languages with<strong>in</strong> a digital text. “We can take exist<strong>in</strong>g language models for
English and Sanskrit and comb<strong>in</strong>e them,” Breuel explicated. “As part of the comb<strong>in</strong>ation, we can tra<strong>in</strong>
or specify the probable locations and frequencies of transitions between the two language models,
correspond<strong>in</strong>g to, for example, isolated foreign words with<strong>in</strong> one language, or long quotations” (Breuel
2009).
As this subsection has <strong>in</strong>dicated, the computational challenges of process<strong>in</strong>g Sanskrit are be<strong>in</strong>g
actively researched, and some of the technical solutions may be adaptable to other historical languages
as well.
Syriac
The Syriac dialect belongs to the Aramaic branch of the Semitic languages and flourished between the
third and seventh centuries AD, although it cont<strong>in</strong>ued to be used as a written language through the
n<strong>in</strong>eteenth century. It has a somewhat smaller body of research <strong>in</strong> terms of document analysis and
recognition than other ancient dialects and languages covered <strong>in</strong> this review, but nonetheless there is an
active and grow<strong>in</strong>g body of research on this topic. Although there are fewer digital texts available <strong>in</strong>
Syriac onl<strong>in</strong>e than for Greek, Lat<strong>in</strong>, Sumerian, or Sanskrit, some texts written <strong>in</strong> this dialect can be
found <strong>in</strong> many papyri and manuscript collections. 66 In addition, a number of pr<strong>in</strong>ted editions and
reference works on Syriac can be found onl<strong>in</strong>e <strong>in</strong> both Google Books and the Internet Archive. 67
Document-recognition work with Syriac has been reported by Bilane et al. (2008), who have
<strong>in</strong>vestigated the use of word-spott<strong>in</strong>g 68 for handwrit<strong>in</strong>g analysis <strong>in</strong> digitized Syriac manuscripts. They
noted that Syriac presents a particularly <strong>in</strong>terest<strong>in</strong>g case for automatic historical-document analysis
because it comb<strong>in</strong>es the word structure and calligraphy of Arabic handwrit<strong>in</strong>g while also be<strong>in</strong>g
<strong>in</strong>tentionally written at an angle. Bilane et al. (2008) used a word-spott<strong>in</strong>g method so that they would
not need to rely on any prior <strong>in</strong>formation or be dependent on specific word or character-segmentation
algorithms. Tse and Bigun (2007) have also reported on work <strong>in</strong> the automatic recognition of Syriac,
with a focus on develop<strong>in</strong>g an <strong>in</strong>itial character-recognition system that can serve as a basel<strong>in</strong>e OCR for
Syriac-Aramaic texts that use the Serto script. Their system does not require the use of segmentation
66 For example, see the Syriac manuscripts available through the Virtual Manuscript Room, http://vmr.bham.ac.uk/Collections/M<strong>in</strong>gana/part/Syriac/
67 See, for example, Breviarium: juxta ritum ecclesiæ Antiochenæ Syrorum (http://books.google.com/booksid=w-UOAAAAQAAJ) <strong>in</strong> Google Books, or
The book of consolations; or, The pastoral epistles; the Syriac text (with both the Syriac text and the English translation) <strong>in</strong> the Internet Archive
(http://www.archive.org/details/bookofconsolatio00ishouoft).
68 Word-spott<strong>in</strong>g is a technique that has also been used with Lat<strong>in</strong> manuscripts and is expla<strong>in</strong>ed <strong>in</strong> detail earlier <strong>in</strong> this paper.