We present a new comprehensive dataset for the unstandardised West-Germanic language Low Saxon covering the last two centuries, the majority of modern dialects and various genres, which will be made openly available in connection with the final version of this paper.
Cross-lingual transfer learning with large multilingual pre-trained models can be an effective approach for low-resource languages with no labeled training data.
Particularly in the PoS-based distances, one can observe all of the 21st century Low Saxon dialects shifting towards the modern majority languages.
This document outlines a PROSPERO pre-registered protocol for a systematic review regarding articulatory changes in speech following oral or orophayrngeal cancer treatment.
We present an articulatory synthesis framework for the synthesis and manipulation of oral cancer speech for clinical decision making and alleviation of patient stress.
This article reports ongoing investigations into phonetic change of dialect groups in the northern Netherlandic language area, particularly the Frisian and Low Saxon dialect groups, which are known to differ in vitality.
For many (minority) languages, the resources needed to train large models are not available.
In this paper we discuss the implications of using machine learning for judicial decision-making in situations where human rights may be infringed.
We show that speech representations extracted from a specific type of neural model (i. e. Transformers) lead to a better match with human perception than two earlier approaches on the basis of phonetic transcriptions and MFCC-based acoustic features.
In this paper, we explore the performance of a linear SVM trained on language independent character features for the NLI Shared Task 2017.
In this paper, we illustrate the integration of an online dialectometric tool, Gabmap, together with an online dialect atlas, the Atlante Lessicale Toscano (ALT-Web).