Creating a Universal Dependencies Treebank of Spoken Frisian-Dutch Code-switched Data

Anouck Braggaar; Rob van der Goot

Abstract

This paper explores the difficulties of annotating transcribed spoken Dutch-Frisian codeswitch utterances into Universal Dependencies. We make use of data from the FAME!
corpus, which consists of transcriptions and
audio data. Besides the usual annotation difficulties, this dataset is extra challenging because of Frisian being low-resource, the informal nature of the data, code-switching and
non-standard sentence segmentation. As a
starting point, two annotators annotated 150
random utterances in three stages of 50 utterances. After each stage, disagreements where
discussed and resolved. An increase of 7.8
UAS and 10.5 LAS points was achieved between the first and third round. This paper will
focus on the issues that arise when annotating
a transcribed speech corpus. To resolve these
issues several solutions are proposed.

Originalsprog	Engelsk
Publikationsdato	25 sep. 2021
Status	Udgivet - 25 sep. 2021
Begivenhed	RESOURCEFUL-2020 : RESOURCEs and representations For Under-resourced Languages and domains - Gothenburg, Gothenburg, Sverige Varighed: 25 nov. 2020 → … https://gu-clasp.github.io/resourceful-2020/

Workshop

Workshop	RESOURCEFUL-2020
Lokation	Gothenburg
Land/Område	Sverige
By	Gothenburg
Periode	25/11/2020 → …
Internetadresse	https://gu-clasp.github.io/resourceful-2020/

Emneord

annotating transcribed speech
Dutch-Frisian codeswitching
Universal Dependencies
low-resource languages
informal data challenges

Adgang til dokumentet

https://arxiv.org/pdf/2102.11152.pdf

Multi-Task Sequence Labeling Under Adverse Conditions
Plank, B. (PI) & van der Goot, R. (CoI)
Amazon.com, Inc.
01/04/2019 → 31/08/2020
Projekter: Projekt › Andet

Citationsformater

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N2 - This paper explores the difficulties of annotating transcribed spoken Dutch-Frisian codeswitch utterances into Universal Dependencies. We make use of data from the FAME!corpus, which consists of transcriptions andaudio data. Besides the usual annotation difficulties, this dataset is extra challenging because of Frisian being low-resource, the informal nature of the data, code-switching andnon-standard sentence segmentation. As astarting point, two annotators annotated 150random utterances in three stages of 50 utterances. After each stage, disagreements wherediscussed and resolved. An increase of 7.8UAS and 10.5 LAS points was achieved between the first and third round. This paper willfocus on the issues that arise when annotatinga transcribed speech corpus. To resolve theseissues several solutions are proposed.

AB - This paper explores the difficulties of annotating transcribed spoken Dutch-Frisian codeswitch utterances into Universal Dependencies. We make use of data from the FAME!corpus, which consists of transcriptions andaudio data. Besides the usual annotation difficulties, this dataset is extra challenging because of Frisian being low-resource, the informal nature of the data, code-switching andnon-standard sentence segmentation. As astarting point, two annotators annotated 150random utterances in three stages of 50 utterances. After each stage, disagreements wherediscussed and resolved. An increase of 7.8UAS and 10.5 LAS points was achieved between the first and third round. This paper willfocus on the issues that arise when annotatinga transcribed speech corpus. To resolve theseissues several solutions are proposed.

KW - annotating transcribed speech

KW - Dutch-Frisian codeswitching

KW - Universal Dependencies

KW - low-resource languages

KW - informal data challenges

KW - annotating transcribed speech

KW - Dutch-Frisian codeswitching

KW - Universal Dependencies

KW - low-resource languages

KW - informal data challenges

M3 - Conference abstract for conference

T2 - RESOURCEFUL-2020<br/>

Y2 - 25 November 2020

ER -

Creating a Universal Dependencies Treebank of Spoken Frisian-Dutch Code-switched Data

Abstract

Workshop

Emneord

Adgang til dokumentet

Fingeraftryk

Projekter

Multi-Task Sequence Labeling Under Adverse Conditions

Citationsformater