# Syllable-, Bigram-, and Morphology-Driven Pseudoword Generation in Greek
## 3 Methods
The filtering process begins with a \"Lexicon check\" that removes any pseudoword that may already exist in the lexicon/lexica it checks with. Next, the \"Repetition check\" applies to discard those pseudowords that contain sequences of repeating letters or sounds exceeding a threshold of two or more consecutive identical letters: this way, words like \(\mathbf{\alpha\alpha\alpha}\) [aaa], \(\mathbf{\alpha\alpha\gamma}\eta\) [aaij], \(\mathbf{\alpha\rho\theta\theta}ov\) [aii0@on] are eliminated. As a side effect, this process excludes words with two consecutive letters, even those permitted in Greek orthography, such as \(\rho\rho\). That is, words like \(\pi\)_novop\(\mathbf{\alpha}\)_ [apura] will be excluded. The same filtering mechanism operates on segments, disallowing words with phonetically identical vowels, but different spelling, e.g., \(\mathbf{\alpha\
u\eta}\) [eeiji], \(\pi\)_novop_ [paoo]. Following pseudoword generation, the process continues with \(n\)-gram validation, during which the application assesses the generated pseudowords for phonotactic acceptability. More precisely, it constructs bigrams and trigrams for each pseudoword. If any of these generated n-grams fail to match words in the lexicon, the pseudoword is marked as phonologically unacceptable and is thus excluded from further analysis. This filter will rule out pseudowords like \(\alpha\rho\mathbf{\theta\theta}\rho\sigma\) [arii@ros], \(\pi\)_novop\(\mathbf{\rho\sigma\sigma}\)_to_ [perexpusto]. Subsequently, the process continues with a comparative analysis stage that measures the similarity between each pseudoword and all words in the reference databases, i.e., GreekLex2.1 and Clean, or any other specified lexical resource. Employing a similarity ratio grounded in the Levenshtein distance [50], SyBig-r-Morph proceeds to this evaluation as follows: \"1 minus the Levenshtein distance divided by the maximum length of the compared words.\" In this formula, the Levenshtein distance is normalized by dividing it by the maximum length of the two words being compared. Then the resulting ratio is subtracted from 1 to generate a similarity score so that a smaller distance yields a higher similarity score between the two words. This step ensures that the final score will range from 0, with no similarity, to 1, a perfect match. Pseudowords exhibiting a high similarity ratio to actual words will be excluded as being too similar to existing ones, e.g., \(\alpha\
u\rho\epsilon\)  
\begin{table}
\begin{tabular}{l} \hline 1: array (49) \\ \hline \(\alpha\), \(\alpha\), \(\alpha\), \(\alpha\), \(\alpha\), \(\alpha\), \(\alpha\), \(\alpha\), \(\alpha\), \(\beta\), \(\beta\), \(\beta\), \(\gamma\), \(\gamma\), \(\delta\), \(\delta\), \(\gamma\), \(\delta\), \(\delta\), \(\delta\), \(\delta\), \(\epsilon\), \(\epsilon\), \([avrio] (cf. \(\alpha\dot{\
u}\rho\upsilon\) ['tomorrow'), \(\alpha\delta\varepsilon\kappa\alpha\) [a@ika] (cf. \(\dot{\alpha}\delta\kappa\alpha\) ['a@ika] 'unfairly'), \(\alpha\gamma\gamma\gamma\varsigma\) [ayoyos] (cf. \(\dot{\alpha}\gamma\)ovoc ['ayonso' 'infertile'), \(\alpha\alpha\delta\alpha\) [ona@a] (cf. \(\alpha\mu\dot{\alpha}\delta\alpha\) ['ma@a] 'team'). This way, the application guarantees that the final output consists of pseudowords distinct from actual words in the Lexicon. In the current version, the cut-off point is set at 0.8. During testing, we observed that lowering this threshold for nouns resulted in pseudonouns significantly dissimilar to existing nouns, while increasing it resulted in pseudowords that closely resembled existing ones. We arrived at this conclusion during a manual evaluation phase discussed in Section 4. Figure 3 illustrates the application's selection dashboard, which includes user-friendly predetermined threshold values for frequency and familiarity, as explained above. It also includes several user-defined parameters, such as the selection of part of speech, the number of syllables, and the number of words.