Phrasis: studies in language and literature

Rosa versus rossa: The acquisition of Italian geminates by native speakers of Dutch BASTIEN DE CLERCQ, ELLEN SIMON & CLAUDIA CROCCO Focusing on the right cue: Perception of voiceless and voiced stops in English by Brazilian learners UBIRATÃ KICKHÖFEL ALVES & CAMILA SAVICZKI MOTTA On the Edge of Acceptability: Arguments for the Syntactic Dependence of the Flemish External Possessor on the Possessee DP LIISA BUELENS & TIJS D’HULSTER The discourse-marking effect of strong pronoun doubling in French AMÉLIE ROCQUET Beware of Belgium. Een linguïstisch-etnografisch onderzoek naar de invloed van meertaligheid op de weergave van politieke complexiteit in de buitenlandberichtgeving over België ASTRID VANDENDAELE, BRAM VERTOMMEN & ELLEN VAN PRAET The polysemic use of body-part terms in Dutch, German and English: a quantitative contrastive analysis FILIP DEVOS & BEATRIJS VERNIERS The acquisition of the English dative alternation by Russian Foreign Language Learners LUDOVIC DE CUYPERE, EVELYN DE COSTER & KRISTOF BATE

Grammaticalisation processes in Flemish sign language

Following Hopper & Traugott (2003 [1993]: 232), grammaticalisation can be defined as “the change whereby lexical items and constructions come in certain linguistic contexts to serve grammatical functions and, once grammaticalized, continue to develop new grammatical functions.” Grammaticalisation processes have not been studied very extensively in sign languages yet. Pfau & Steinbach (2006) give a very interesting survey of studies that have focused on grammaticalisation processes in sign languages, but Flemish Sign Language (VGT) was not one of them. Within the Deaf community in Flanders about 5000 - 6000 people (Loots et al. 2003) claim to have Flemish Sign Language as their first or principal language. After lengthy negotiations, VGT was officially recognized by the Flemish Parliament in April 2006. VGT clearly is a fully-fledged sign language in its own right, and is genealogically related to amongst others French-Belgian Sign Language (LSBF), French Sign Language (LSF), American Sign Language (ASL) and Sign Language of the Netherlands (NGT). The common ancestor of these daughter sign languages is Old French Sign Language (OFSL). However, it is impossible to use historical data to look at grammaticalisation paths since there simply are very few historical grammatical data as OFSL was never written down. Consequently, the method to be used is that of internal reconstruction which is a procedure for inferring part of the history of a language from material available for a synchronic description of the language on the basis of paradigmatic allomorphy

The relation between orthography and phonology

B

The effect of L1 regional variation on the perception and production of standard L1 and L2 vowels

This study reports on the perception and production of Standard Dutch and Standard British English vowels by speakers of two regional varieties of Belgian Dutch (East Flemish and Brabantine) which differ in their vowel realizations. Twenty-four native speakers of Dutch performed two picture-naming tasks and two vowel categorization tasks, in which they heard Standard Dutch or English vowels and were asked to map these onto orthographic representations of Dutch vowels. The results of the Dutch production and categorization tasks revealed that the participants’ L1 regional variety importantly influenced their production and especially perception of vowels in the standard variety of their L1. The two groups also differed in how they assimilated non-native English vowels to native vowel categories, but no major differences could be observed in their productions of non-native vowels. The study therefore only partly confirms earlier studies showing that L1 regional variation may have an influence on the acquisition of non-native language varieties

Towards automatic sign language corpus annotation using deep learning

Sign classification in sign language corpora is a challenging problem that requires large datasets. Unfortunately, only a small portion of those corpora is labeled. To expedite the annotation process, we propose a gloss suggestion system based on deep learning. We improve upon previous research in three ways. Firstly, we use a proven feature extraction method called OpenPose, rather than learning end-to-end. Secondly, we propose a more suitable and powerful network architecture, based on GRU layers. Finally, we exploit domain and task knowledge to further increase the accuracy. We show that we greatly outperform the previous state of the art on the used dataset. Our method can be used for suggesting a top 5 of annotations given a video fragment that is selected by the corpus annotator. We expect that it will expedite the annotation process to the benefit of sign language translation research

Sign language recognition with transformer networks

Sign languages are complex languages. Research into them is ongoing, supported by large video corpora of which only small parts are annotated. Sign language recognition can be used to speed up the annotation process of these corpora, in order to aid research into sign languages and sign language recognition. Previous research has approached sign language recognition in various ways, using feature extraction techniques or end-to-end deep learning. In this work, we apply a combination of feature extraction using OpenPose for human keypoint estimation and end-to-end feature learning with Convolutional Neural Networks. The proven multi-head attention mechanism used in transformers is applied to recognize isolated signs in the Flemish Sign Language corpus. Our proposed method significantly outperforms the previous state of the art of sign language recognition on the Flemish Sign Language corpus: we obtain an accuracy of 74.7% on a vocabulary of 100 classes. Our results will be implemented as a suggestion system for sign language corpus annotation