1 code implementation • ACL 2022 • Wietse de Vries, Martijn Wieling, Malvina Nissim
Cross-lingual transfer learning with large multilingual pre-trained models can be an effective approach for low-resource languages with no labeled training data.
no code implementations • VarDial (COLING) 2020 • Janine Siewert, Yves Scherrer, Martijn Wieling, Jörg Tiedemann
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.
no code implementations • LChange (ACL) 2022 • Janine Siewert, Yves Scherrer, Martijn Wieling
Particularly in the PoS-based distances, one can observe all of the 21st century Low Saxon dialects shifting towards the modern majority languages.
2 code implementations • 22 May 2023 • Wietse de Vries, Martijn Wieling, Malvina Nissim
The benchmark includes a diverse set of datasets for low-, medium- and high-resource tasks.
1 code implementation • 18 May 2023 • Martijn Bartelds, Nay San, Bradley McDonnell, Dan Jurafsky, Martijn Wieling
For Gronings, for which there was a pre-existing text-to-speech (TTS) system available, we also examined the use of TTS to generate ASR training data from text-only sources.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +2
no code implementations • 14 Sep 2022 • Thomas B. Tienkamp, Teja Rebernik, Defne Abur, Rob J. J. H. van Son, Sebastiaan A. H. J. de Visscher, Max J. H. Witjes, Martijn Wieling
This document outlines a PROSPERO pre-registered protocol for a systematic review regarding articulatory changes in speech following oral or orophayrngeal cancer treatment.
1 code implementation • NAACL 2022 • Martijn Bartelds, Martijn Wieling
Deep acoustic models represent linguistic information based on massive amounts of data.
no code implementations • 31 Mar 2022 • Bence Mark Halpern, Teja Rebernik, Thomas Tienkamp, Rob van Son, Michiel van den Brekel, Martijn Wieling, Max Witjes, Odette Scharenborg
We present an articulatory synthesis framework for the synthesis and manipulation of oral cancer speech for clinical decision making and alleviation of patient stress.
no code implementations • 15 Oct 2021 • Raoul Buurke, Hedwig Sekeres, Wilbert Heeringa, Remco Knooihuizen, Martijn Wieling
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.
1 code implementation • Findings (ACL) 2021 • Wietse de Vries, Martijn Bartelds, Malvina Nissim, Martijn Wieling
For many (minority) languages, the resources needed to train large models are not available.
no code implementations • 18 Dec 2020 • Masha Medvedeva, Martijn Wieling, Michel Vols
In this paper we discuss the implications of using machine learning for judicial decision-making in situations where human rights may be infringed.
1 code implementation • 25 Nov 2020 • Martijn Bartelds, Wietse de Vries, Faraz Sanal, Caitlin Richter, Mark Liberman, Martijn Wieling
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.
no code implementations • CL 2018 • Martijn Wieling, Josine Rawee, Gertjan van Noord
For a selection of ten papers, we attempted to reproduce the results using the provided data and code.
no code implementations • WS 2017 • Artur Kulmizev, Bo Blankers, Johannes Bjerva, Malvina Nissim, Gertjan van Noord, Barbara Plank, Martijn Wieling
In this paper, we explore the performance of a linear SVM trained on language independent character features for the NLI Shared Task 2017.
no code implementations • LREC 2016 • Martijn Wieling, Eva Sassolini, Sebastiana Cucurullo, Simonetta Montemagni
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).