A Comparison of Different Machine Transliteration Models
Table 14: Main characteristics obtained from Figures 3 and 4.
['[EMPTY]', 'EKSet', 'EJSet']
The figures show that, as the area of intersection between different transliteration models becomes smaller, the size of their union tends to become bigger. The first thing to note is that |ψG∩ψP| is clearly smaller than any other intersection. The main reason for this is that ψG and ψP use no common information (ψG uses source graphemes while ψP uses source phonemes). However, the others use at least one of source grapheme and source phoneme (source graphemes are information common to ψG, ψH, and ψC while source phonemes are information common to ψP, ψH, and ψC). Therefore, we can infer that the synergy derived from combining ψG and ψP is greater than that derived from the other combinations. The main reason for this might be the higher transliteration power of ψC and ψH compared to that of ψG and ψP – ψC and ψH cover more of the KTG and JTG than both ψG and ψP. The second thing to note is that the contribution of each transliteration model to |ψG ∪ ψP ∪ ψH ∪ ψC| can be estimated from the difference between |ψG ∪ ψP ∪ ψH ∪ ψC| and the union of the three other transliteration models. For example, we can measure the contribution of ψH from the difference between |ψG ∪ ψP ∪ ψH ∪ ψC| and |ψG ∪ ψP ∪ ψC|. The main reason for ψH making the smallest contribution is that it tends to produce the same transliteration as the others, so the intersection between ψH and the others tends to be large.