By Jörg Tiedemann
This ebook offers an summary of assorted strategies for the alignment of bitexts. It describes basic innovations and methods that may be utilized to map corresponding elements in parallel records on quite a few degrees of granularity. Bitexts are necessary linguistic assets for plenty of diversified study fields and sensible purposes. the main major program is laptop translation, specifically, statistical computer translation. even if, there are lots of different threads that may be that could be supported by means of the wealthy linguistic wisdom implicitly kept in parallel assets. Bitexts were explored in lexicography, observe experience disambiguation, terminology extraction, computer-aided language studying and translation stories to call quite a few. The publication covers the fundamental initiatives that experience to be performed whilst development parallel corpora ranging from the gathering of translated records as much as sub-sentential alignments. specifically, it describes a variety of methods to record alignment, sentence alignment, observe alignment and tree constitution alignment. it is also an inventory of assets and a accomplished evaluate of the literature on alignment thoughts. desk of Contents: creation / easy ideas and Terminology / development Parallel Corpora / Sentence Alignment / notice Alignment / word and Tree Alignment / Concluding feedback
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Additional info for Bitext Alignment (Synthesis Lectures on Human Language Technologies)
STRAND uses language-specific boolean search queries to find such web sites, for example: (anchor:"english" OR anchor:"anglais") AND (anchor:"french" OR anchor:"francais"). The system applies simple regular expressions to filter candidates pages by looking for web sites with language links close to each other. Sibling documents are web sites that include links to translations of the same page. Again, boolean search queries (anchor:"english" OR anchor:"anglais") can be used to obtain a candidate list of such pages.
Various well-known instances of dynamic programming exist (for example, the Viterbi algorithm) depending on the data structure and the underlying model employed. 20 2. BASIC CONCEPTS AND TERMINOLOGY Global dynamic programming solutions can often be approximated using more efficient (but suboptimal) beam search strategies. Greedy best-first: A very efficient heuristic search strategy is greedy optimization. In this strategy, an algorithm selects greedily the best local choice and continues iteratively with the remaining decisions.
However, many-to- 38 4. SENTENCE ALIGNMENT many mappings are usually allowed but often dispreferred. The atomic unit in sentence alignment is, naturally, a sentence but, in a broad sense, including sentence fragments or other textual elements such as headers, lists or table cells. The input to a sentence alignment algorithm is a bitext, and the output is the mapping between corresponding sentences. 1). Simple cues such as length correlations and incomplete lexical constraints are often sufficient to perform reasonably well.