Learning to Translate: A Statistical and Computational Analysis

<table class="table-group" id="tab3"><tr><td><table class="table"><tr><td class="thead-hr" colspan="4"><hr/></td></tr><tr class="thead"><td align="left">Language pairs</td><td align="center">Data</td><td align="center">SMT system</td><td align="center">No. random subsets</td></tr><tr><td class="thead-hr" colspan="4"><hr/></td></tr><tr><td align="left"><span style="width: 54.049999px;"><svg height="11.375" id="M61" style="vertical-align:-0.1638pt" version="1.1" viewbox="0 0 54.049999 11.375" width="54.049999" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
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</svg></span></td><td align="center">Europarl</td><td align="center">Moses</td><td align="center">
												10
												</td></tr><tr><td align="left"><span style="width: 54.049999px;"><svg height="11.375" id="M62" style="vertical-align:-0.1638pt" version="1.1" viewbox="0 0 54.049999 11.375" width="54.049999" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
<g transform="matrix(.017,0,0,-.017,.062,11.113)"><path d="M609 650l-19 -162l-30 -2q2 69 -14 94q-9 18 -28.5 26t-74.5 8h-88q-30 0 -37 -6.5t-12 -36.5l-41 -212h103q48 0 69 5.5t32 19t26 50.5h29l-40 -198h-30q2 58 -11.5 70.5t-85.5 12.5h-99l-30 -167q-17 -87 3 -101q18 -15 111 -15q59 0 89 7t54 27q8 7 15.5 16t16 21.5
l14 20.5t15 23.5t13.5 21.5l29 -10q-52 -129 -71 -163h-500l6 28q66 4 83 17.5t28 73.5l77 409q11 61 -0.5 75.5t-78.5 18.5l10 28h467z" id="x1D438"></path></g><g transform="matrix(.017,0,0,-.017,10.806,11.113)"><path d="M352 391q0 -31 -27 -44q-14 -7 -24 6q-39 48 -84 48q-23 0 -39.5 -15t-16.5 -40q0 -43 73 -90q49 -32 70 -58t21 -57q0 -58 -62 -105.5t-129 -47.5q-40 0 -75.5 25t-35.5 52q0 28 32 46q7 4 15 3t11 -6q19 -31 48.5 -50.5t54.5 -19.5q34 0 54 19.5t20 42.5q0 43 -65 81
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</svg></span></td><td align="center">Europarl</td><td align="center">Portage</td><td align="center">
												10
												</td></tr><tr><td align="left"><span style="width: 54.674999px;"><svg height="11.375" id="M63" style="vertical-align:-0.1638pt" version="1.1" viewbox="0 0 54.674999 11.375" width="54.674999" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
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</svg></span></td><td align="center">Giga</td><td align="center">Moses</td><td align="center">
												3
												</td></tr><tr><td align="left"><span style="width: 57.962502px;"><svg height="12.4375" id="M64" style="vertical-align:-0.1638pt" version="1.1" viewbox="0 0 57.962502 12.4375" width="57.962502" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
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</svg></span></td><td align="center">UN</td><td align="center">Portage</td><td align="center">
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											</td></tr><tr class="table-tr"><td colspan="4"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

Different settings used to create the Learning Curves. Due to the large dimension of the Giga corpus, only three random subsets have been built.

Advances in Artificial Intelligence

Learning to Translate: A Statistical and Computational Analysis

Table 3