Download Bitext Alignment (Synthesis Lectures on Human Language by Jörg Tiedemann PDF

By Jörg Tiedemann

ISBN-10: 1608455106

ISBN-13: 9781608455102

This ebook presents an outline of assorted thoughts for the alignment of bitexts. It describes basic suggestions and techniques that may be utilized to map corresponding elements in parallel files on quite a few degrees of granularity. Bitexts are important linguistic assets for plenty of varied examine fields and sensible functions. the main fundamental program is desktop translation, specifically, statistical computing device translation. besides the fact that, there are lots of different threads that may be that could be supported by way of the wealthy linguistic wisdom implicitly kept in parallel assets. Bitexts were explored in lexicography, note feel disambiguation, terminology extraction, computer-aided language studying and translation experiences to call quite a few. The booklet covers the basic initiatives that experience to be performed while development parallel corpora ranging from the gathering of translated records as much as sub-sentential alignments. particularly, it describes numerous ways to record alignment, sentence alignment, note alignment and tree constitution alignment. it is also an inventory of assets and a entire evaluation of the literature on alignment innovations. desk of Contents: advent / easy options and Terminology / development Parallel Corpora / Sentence Alignment / notice Alignment / word and Tree Alignment / Concluding comments

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Additional resources for Bitext Alignment (Synthesis Lectures on Human Language Technologies)

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They assume that the number of characters generated follows a pre-defined distribution, independent of type and context. 06 for French/English). They also plotted the frequencies of length differences in their aligned parallel data in order to check the density distribution, which in their case was approximately normal. 8) estimated from the same data. For simplicity, these values are fixed in the general algorithm proposed by Gale and Church [1991b]; therefore, no additional training data is required to optimize those parameters when ap- 40 4.

Their model describes the process of generating characters in the target language from characters in the source language. They assume that the number of characters generated follows a pre-defined distribution, independent of type and context. 06 for French/English). They also plotted the frequencies of length differences in their aligned parallel data in order to check the density distribution, which in their case was approximately normal. 8) estimated from the same data. For simplicity, these values are fixed in the general algorithm proposed by Gale and Church [1991b]; therefore, no additional training data is required to optimize those parameters when ap- 40 4.

1 shows an example for an XML-based stand-off annotation of sentence alignment. Keeping separate alignment files has many advantages. For example, it is possible to combine several parallel documents into one bitext as we can see in the example. Furthermore, alternative alignments can be stored simply by creating additional stand-off alignment files. Certain alignment types can easily be filtered out (for example non-one-to-one mappings when processing a bitext). Finally, it is also straightforward to create alignments between multiple documents (for example, translations into various languages) without repeating any document content.

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Bitext Alignment (Synthesis Lectures on Human Language Technologies) by Jörg Tiedemann


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