Abstract
In this paper we present the first-ever procedure for identifying highly similar sequences of text in Chinese and Tibetan translations of Buddhist <em>sūtra</em> literature. We initially propose this procedure as an aid to scholars engaged in the philological study of Buddhist documents. We create a cross-lingual embedding space by taking the cosine similarity of average sequence vectors in order to produce unsupervised similar cross-linguistic parallel alignments at word, sentence, and even paragraph level. Initial results show that our method lays a solid foundation for the future development of a fully-fledged Information Retrieval tool for these (and potentially other) low-resource historical languages.
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