# Syllable-, Bigram-, and Morphology-Driven Pseudoword Generation in Greek
## 3 Methods
The latter value is set to 1000, the maximum number of words allowed in the application's current settings. Importantly, users can view and select either all syllables or only those appearing in the word-final position, allowing them to determine specific noun classes or verb voice based on word endings. This is a crucial feature because it allows users to precisely control the grammatical properties of generated pseudowords. Furthermore, users can also decide to either include or exclude words with marginal word-final phonotactics, such as those ending in consonants other than /n/ and /s/, which are the only word-final consonants phonotactically permitted in Greek. Figure 3: Detailed pseudoword generation interface. Expanded interface showing generation parameters for Greek pseudowords with noun selection (3 syllables), frequency threshold (5.0), and similarity threshold (0.8). The last syllable selection panel displays available Greek syllables (64 of 71 selected) with options to select/deselect all or search specific syllables. The interface is configured to generate up to 1000 pseudowords. As shown in Figure 4, the \"Status\" panel below the pseudoword generation button provides users with comprehensive information about their selections and the pseudoword generation process. During initialization, it displays the lexicon loading process and parameters, including part-of-speech specification (noun), syllable count (3), and threshold settings (frequency: 4.327, similarity: 0.8). Once processing begins, the system reports the distribution of syllables across three positions, identifying 121 initial, 159 medial, and 71 final syllables. Following Greek phonotactic constraints, the panel indicates that 64 of the 71 final syllables were selected, with endings from loanwords and archatic forms being systematically excluded. Throughout the generation phase, the interface provides real-time progress updates, tracking incremental production in sets of 5 pseudowords from the initial batch to the final target of 1,000. In this demonstration, the entire process was completed in approximately 19 seconds (01:06:24 to 01:06:43), achieving an average generation rate of 53 words per second. The panel concludes with a completion message confirming the successful generation of all requested pseudowords. Figure 4: Cont. When the set of available syllables is particularly limited, however, identical outputs are more likely. For example, generating 15 non-passive verb forms ending in -/-zo with the same settings resulted in multiple duplicates, as follows: _votetevu_, _m#anu_, _m#anu_, _votetvu_, _votetvu_, _votetvu_, _m#anu_, _m#anu_, _m#anu_, _m#anu_, _m#anu_, _n#anu_, _n#anu_, _n#anu_, _votetvu_, _votetvu_, _m#o#anu_, _m#anu_, This occurred because the only available final syllables in the syllable set were \(\zeta\omega\) (/zo/) and \(\omega\) (/o/). Nevertheless, if users wish to reproduce the same results, they can ensure consistency by adding the following command at the beginning of the sybig-r-morph-gui.py script:  
np.random.seed(seed=12345678)  
The \"Generated Pseudowords\" panel of the application displays the pseudowords. This section of the interface includes four control buttons: \"Sort A-Z\", which organizes the pseudonumnous in alphabetical order; \"Randomize\", which shuffles their arrangement; \"Copy All\", which copies the words to the clipboard; and \"Download CSV\", which allows users to export the data. Users can manually reorganize words using a drag-and-drop  
Figure 4: **(a,b)** Pseudoword generation process and performance metrics. (**a**) Status panel showing the lexicon loading process and the initialization parameters for pseudoword generation; (**b**) completion of pseudoword generation task and user interface for generated Greek pseudowords with management controls. Generation of 1000 three-syllable noun pseudowords using 64 selected final syllables from a corpus analysis (121 initial, 159 medial, 71 final syllables identified). Parameters: frequency threshold 4.327, similarity threshold 0.8.