# Developing a Hybrid Morphological Analyzer for Low-Resource Languages
## 3 Methodology
### Dataset Creation
#### 3.1.3 Paradigm Generation
The proposed morphological analyzer of Kannada nouns shows the details of the root word, gender, number and case. The declension forms for the masculine noun _huduga_ (boy) are depicted in Table 8. \begin{table}
\begin{tabular}{c c c} \hline
**Type** & **Stems** & **Inflections** \\ \hline Noun & 7873 & 173,740 \\ Verb & 956 & 30,725 \\ Indeclinable & 242 & 242 \\ Adjective & 799 & 799 \\ Numeric & 9 & 9 \\ Pronoun & 12 & 144 \\ \hline
**Total** & **9891** & **205,659** \\ \hline \end{tabular}
\end{table} 
Table 7: Word classification with the count of stems and generated inflections. \begin{table}
\begin{tabular}{c c c} \hline
**Case** & **Singular Form** & **Plural Form** \\ \hline Nominative & _huduganu_ / & _huduganu_ \\  & _huduga_ \\ Accusative & _huduganannu_ & _hudugarannu_ \\ Instrumental & _huduganliMxa_ & _hudugariMxa_ \\ Dative & _huduganigeV_ / & _hudugarigeV_ / \\  & _huduganigAggi_ / & _hudugarigAggi_ / \\  & _huduganigoskara_ & _hudugarigoskara_ \\ Ablative & _hudugana deVseVyiMxa_ / & _hudugara deVseVyiMxa_ / \\  & _huduganiMxa_ & _hudugariMxa_ \\ Genitive & _hudugana_ & _hudugana_ \\ \hline \end{tabular}
\end{table} 
Table 8: Declension forms for the word _huduga_. The declension is used to build the paradigm with categorization on linguistic features. Several other masculine nouns ending with \(a\) like _yuvaka_, _muxuxa_, etc., follow the pattern of declension forms as that of _huduga_. On the whole, there are certain exceptions, and they have to be manually fed into the system. Furthermore, the exceptions are also found in various POSs like verbs, such as _geVllu_, that do not follow the same paradigm. The exceptions handled by the system require separate paradigms designed for them, as highlighted in Table 9. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Case** & **Singular Form** & **Plural Form** \\ \hline Locative & _huduganalli_ & _hudugaralli_ \\ Vocative & _hudugane_ / & _hudugare_ \\  & _hudugA_ & \\ \hline \hline \end{tabular}
\end{table} 
Table 8: _Cont._ \begin{table}
\begin{tabular}{c c c} \hline \hline
**Word** & **Type** & **Total Count** \\ \hline _AyA_ & & \\ _sarvAMuvaryAmi_ & & \\ _Sri_ & & \\ _ssurrl_ & & \\ _sAXu_ & & \\ _magu_ & & \\ _hUI_ & & \\ _go_ & & \\ _x0 VreV_ & & \\ _patAlaM_ & & \\ \hline _nAnu_ & & \\ _n1 tu_ & & \\ _aavun_ & & \\ _aavliu_ & & \\ _aavu_ & & \\ _axu_ & & \\ _ixu_ & & \\ _ixu_ & & \\ _ixu_ & & \\ _ixu_ & & \\ _ixu_ & & \\ _Iua_ & & \\ \hline _bagi_ & & \\ _huyqi_ & & \\ _avi_ & & \\ _sqi_ & & \\ _toyu_ & & \\ _iru_ & & \\ _iMgu_ & & \\ _geVllu_ & & \\ _kAyu_ & & \\ _elYu_ & & \\ _koVllu_ & & \\ _nMaNru_ & & \\ _nillu_ & & \\ _bawwu_ & & \\ _baru_ & & \\ _mlyu_ & & \\ _soMku_ & & \\ _hoVrnu_ & & \\ _hoVrnu_ & & \\ _eVlaku_ & & \\ _bE_ & & \\ \hline \hline \end{tabular}
\end{table} 
Table 9: Exception paradigm statistics. The developed morphological analyzer can obtain the analysis for words present in the dictionary based on the paradigms coded. However, it is limited to known words. As new words keep being added to the dictionary, it is impossible to manually categorize all the words. This limitation is overcome by the Transformer architecture, a model trained on the nouns in the generated dataset. The nouns are used to train the model due to its volume in the morphological analysis data compared to other POS categories. The OpenNMT toolkit is used for generating the analysis [39, 40] and Transformer architectures [19] to train the Apertium data. The model is trained for 10,000 steps, where a stable result was achieved. The evaluation metrics are coded using Python 3.8. We have modeled the morphological analysis generation similar to a translation task, where source and target sides are replaced by LHS and RHS files. ## 5 Discussion and Analysis of Results

The Kannada dictionary dataset with 11,005 words is considered in this study. After pre-processing, a total of 9879 stems are extracted [37]. The stems are classified into nouns, verbs, indeclinables, adjectives, numeric words, and pronouns.