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Bilingual Document Alignment with Latent Semantic Indexing ...
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Abstract:
We apply cross-lingual Latent Semantic Indexing to the Bilingual Document Alignment Task at WMT16. Reduced-rank singular value decomposition of a bilingual term-document matrix derived from known English/French page pairs in the training data allows us to map monolingual documents into a joint semantic space. Two variants of cosine similarity between the vectors that place each document into the joint semantic space are combined with a measure of string similarity between corresponding URLs to produce 1:1 alignments of English/French web pages in a variety of domains. The system achieves a recall of ca. 88% if no in-domain data is used for building the latent semantic model, and 93% if such data is included. Analysing the system's errors on the training data, we argue that evaluating aligner performance based on exact URL matches under-estimates their true performance and propose an alternative that is able to account for duplicates and near-duplicates in the underlying data. ... : Proceedings of the First Conference on Machine Translation (2016), Volume 2: Shared Task Papers ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences
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URL: https://arxiv.org/abs/1707.09443
https://dx.doi.org/10.48550/arxiv.1707.09443
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