Differences
This shows you the differences between two versions of the page.
| Both sides previous revision Previous revision Next revision | Previous revision | ||
|
courses:rg:overcoming_vocabulary_sparsity_in_mt_using_lattices [2010/11/30 11:21] popel my comments |
courses:rg:overcoming_vocabulary_sparsity_in_mt_using_lattices [2011/01/09 19:43] (current) kirschner |
||
|---|---|---|---|
| Line 25: | Line 25: | ||
| The strong side of the proposed approaches is that these techniques work for large training data. | The strong side of the proposed approaches is that these techniques work for large training data. | ||
| + | |||
| + | ==== Remarks by Martin Kirschner ==== | ||
| + | * The experiments and evaluation are done on Arabic-English translation pair. | ||
| + | * Section 2 of the paper: //Many of the above works use morphological toolkits, while in this work we explore lightweight techniques that use the parallel data as the main source of information. We are able to combine both linguistic and statistical sources knowledge and then train the system to select which information it will use at decoding time.// - What is the difference between morphological toolkits and linguistic and statistical sources of knowledge? Is it the reason why the don't use lemmatizer (as mentioned above), to do the work mork lightweight? | ||
| ===== Challenge 1 ===== | ===== Challenge 1 ===== | ||
| Line 76: | Line 80: | ||
| They can work with prefixes b-, l-, Al- and k- using similar approach as for w- prefix. | They can work with prefixes b-, l-, Al- and k- using similar approach as for w- prefix. | ||
| They can look at the context for spelling correction. | They can look at the context for spelling correction. | ||
| - | |||