# Morphological Analysis for the Maltese Language: The Challenges of a Hybrid System

arXiv: https://arxiv.org/abs/1703.08701 · HTML: https://mlsanity.com/paper/1703.08701/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 25 Mar 2017.

## Built on by (most cited first, 2 of 2)

- [Analysis of Data Augmentation Methods for Low-Resource Maltese ASR](https://mlsanity.com/paper/2111.07793/) (2021)
- [LV-ROVER-MLT: Low-Resource Maltese OCR by Synthetic Fine-Tuning and Multi-Stream Arbitration](https://mlsanity.com/paper/2607.00250/) (2026)

## Abstract (arXiv)

Maltese is a morphologically rich language with a hybrid morphological system which features both concatenative and non-concatenative processes. This paper analyses the impact of this hybridity on the performance of machine learning techniques for morphological labelling and clustering. In particular, we analyse a dataset of morphologically related word clusters to evaluate the difference in results for concatenative and nonconcatenative clusters. We also describe research carried out in morphological labelling, with a particular focus on the verb category. Two evaluations were carried out, one using an unseen dataset, and another one using a gold standard dataset which was manually labelled. The gold standard dataset was split into concatenative and non-concatenative to analyse the difference in results between the two morphological systems.