## 4 Results
The phonetic frequency list file contains 19,43,458 Polish words written orthographically, their phonetic transcriptions in the SAMPA phonemic alphabet, and additionally the number of each word occurring in the NCP source corpus. The total number of word-tokens in the NCP corpus is 230,300,300. This describes a plain text version of the NCP corpus file containing 230 million words in Polish. It should also be noted that, the standard SAMPA transcriptions for Polish include several sequences of phonetic transcription labels that may cause ambiguity unless separated by spaces or other characters. To avoid this problem, the individual phonemes were separated by square brackets. Making the developed rule-based implementation available could be very useful to the community--both for linguistic research and for more in-depth performance comparisons between the current rule-based solution and others. Therefore, it is planned to make TransFon application available after making necessary corrections in the implemented algorithm and determining the conditions and license of making the application available for other users. ```
7692997w[t]
53332101[i]
4235003 ma[ma]
4158902z[s]
3981525 sig[t\"e]
3601719 nie[n\"e]
2904114 do[do]
22025896 ke[ze]
2171877 to[t\"o]
1713104e[o]
1728527 jseat[jest]
1425793[a]
1003207 jzk[jask]
983395 po[po]
912660 ed[ot]
877522 ale[ale]
847373 zz[sz]
775006 prze[pses]
7540240c[tos]
663771 di[al3]
646573z[st]
610035 tym[t1m]
606763 jw[juss]
544429 sa[soe\"]
54434 ak[tak]
534509 style[tl%o]
500801 ma[ma]
475172 mozie[moZe]
451225 tegeg[tgeo]
445705z[ze]
426201 jego[jego]
41385 erraz[rosan]
392445 bo[bo]
390741 kd[twhere]
386863 yd[ben\"dZ\"e]
376600 ich[ix]
36722 ale[tje]
385928 hy[0h]
38570 eu[te%s]
3857026 yt[kurt]
349641 jeszcz[jesStSe]
38423 ybz[bl\"]
384560 yt[bt\"]
345596 jedank[jedank]
342989 przy[ps1]...
```

Listing 3: A sample fragment of the frequency list file of the phonemic language corpus developed for Polish

## 5 Statistical Approach

Various grapheme-to-phoneme conversion methods can be used, but three types are most important and most often used: rule-based methods, dictionary-based methods, and statistical methods [51]. Rule-based grapheme-to-phoneme conversion methods may be complemented by dictionary-based and statistical methods. The rule-based grapheme-to-phoneme conversion system discussed in this paper was complemented by the dictionary-based method. Statistical methods can also improve grapheme-to-phoneme conversion for Polish in the future. For this purpose, the author performed statistical analysis of the grapheme-to-phoneme conversion rules in Polish. For better analysis of the obtained results, a special naming scheme for conversion rules was adopted. The naming conventions of the grapheme-to-phoneme conversion rules were as follows:

\[R_{i}=\text{L\_R\_C\_P} \tag{32}\]

where: \(R_{i}\) is the name of the rule, \(\text{L}\) is an orthographic letter to which the rule applies, \(\text{R}\) is a row number in the grapheme-to-phoneme conversion table, \(\text{C}\) is a column number in the grapheme-to-phoneme conversion table, and \(\text{P}\) is a phonemic letter, to which the rule applies. A sample list of grapheme-to-phoneme conversion rules for letter \"a\" using these naming conventions is presented in Table 21.

The frequency of each \(R_{i}\) grapheme-to-phoneme conversion rule was calculated during automatic grapheme-to-phoneme conversion of an orthographic text corpus file in Polish containing 1,843,069,533 letters, obtained from the National Corpus of Polish. A sample list of the most frequently used grapheme-to-phoneme conversion rules in Polish is presented in Table 22.

The frequencies of grapheme-to-phoneme conversion rules used in Polish are presented in Figure 2.