Analyses of Script: Properties of Characters and Writing by Altmann, Gabriel, Gabriel Altmann

By Altmann, Gabriel, Gabriel Altmann

This quantity provides 12 papers on a brand new method of the research of writing structures. For the 1st time, quantitative equipment are brought into this sector of analysis in a scientific manner. the person contributions provide an outline approximately quantitative homes of symbols and of writing structures, introduce equipment of study, learn person writing platforms as used for various languages, manage an explanatory version of phenomena attached to script development/evolution, and provides a viewpoint to a normal thought of writing platforms.

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Additional resources for Analyses of Script: Properties of Characters and Writing Systems (Quantitative Linguistics) (German Edition)

Example text

Another problem was the representation of a phoneme by zero grapheme. For example ABLER has the pronunciation of /ey b ah l er/, in which /ah/ is present phonemically but not graphemically. These cases are interpreted as /ah/ being part of if stays in front of (also

  • ) and 28 Fan Fengxiang and Gabriel Altmann marked as /ah/ → ∈ . There are several cases of this sort as can be seen in Table 9 (see p. ). The following are the first ten cases of the automatic graphemic separation and grapheme-phoneme mapping by the computer.

    In order to illustrate the computation, we use the representations of /TH/, where there are N = 741 cases distributed to graphemic variants in proportions: 1, 736, 3, 1. 0676 . Though there are four graphemic variants, the uncertainty is very low, because one of them,

    , occurs in the great majority of cases. Consequently, even if K or H0 are great, H1 yields a more adequate picture of uncertainty/diversity. The results are presented in the fourth column of Table 2. H0 and H1 are characteristics of uncertainty/diversity.

    This can be of two sorts: one based on the dictionary and the other based on texts. If one of the representations occurs 1 000 times, it is surely more relevant than one occurring only once. Hence, another measure of uncertainty is the entropy of first order taking into account the relative frequencies of individual representations. Usually one uses the Shannon entropy defined as K H1 = − ∑ pi log2 pi (2) i=1 where K is the number of representations and we estimate pi by fi /N, where fi is the absolute frequency, N being the number of occurrences of representations of the given phoneme (N = Σ fi ).

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