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Found 13 papers, 4 papers with code
Crowd-sourcing evaluation of automatically acquired, morphologically related word groupings
The automatic discovery and clustering of morphologically related words is an important problem with several practical applications.
Morphological Analysis for the Maltese Language: The Challenges of a Hybrid System
In particular, we analyse a dataset of morphologically related word clusters to evaluate the difference in results for concatenative and nonconcatenative clusters.
Face2Text: Collecting an Annotated Image Description Corpus for the Generation of Rich Face Descriptions
To gain a better understanding of the variation we find in face description and the possible issues that this may raise, we also conducted an annotation study on a subset of the corpus.
CUNI--Malta system at SIGMORPHON 2019 Shared Task on Morphological Analysis and Lemmatization in context: Operation-based word formation
This paper presents the submission by the Charles University-University of Malta team to the SIGMORPHON 2019 Shared Task on Morphological Analysis and Lemmatization in context.
Creating Expert Knowledge by Relying on Language Learners: a Generic Approach for Mass-Producing Language Resources by Combining Implicit Crowdsourcing and Language Learning
We introduce in this paper a generic approach to combine implicit crowdsourcing and language learning in order to mass-produce language resources (LRs) for any language for which a crowd of language learners can be involved.
MASRI-HEADSET: A Maltese Corpus for Speech Recognition
Maltese, the national language of Malta, is spoken by approximately 500, 000 people.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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On the Language-specificity of Multilingual BERT and the Impact of Fine-tuning
Recent work has shown evidence that the knowledge acquired by multilingual BERT (mBERT) has two components: a language-specific and a language-neutral one.
Analysis of Data Augmentation Methods for Low-Resource Maltese ASR
Recent years have seen an increased interest in the computational speech processing of Maltese, but resources remain sparse.
Pre-training Data Quality and Quantity for a Low-Resource Language: New Corpus and BERT Models for Maltese
We also present a newly created corpus for Maltese, and determine the effect that the pre-training data size and domain have on the downstream performance.
Face2Text revisited: Improved data set and baseline results
To encourage the development of more human-focused descriptions, we developed a new data set of facial descriptions based on the CelebA image data set.
Cross-Lingual Transfer from Related Languages: Treating Low-Resource Maltese as Multilingual Code-Switching
Although multilingual language models exhibit impressive cross-lingual transfer capabilities on unseen languages, the performance on downstream tasks is impacted when there is a script disparity with the languages used in the multilingual model's pre-training data.
National Language Technology Platform (NLTP): overall view
The work in progress on the CEF Action National Language Technology Platform (NLTP) is presented.
National Language Technology Platform for Public Administration
This article presents the work in progress on the collaborative project of several European countries to develop National Language Technology Platform (NLTP).
