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.

Original language	English
Publication date	25 Sept 2021
Publication status	Published - 25 Sept 2021
Event	RESOURCEFUL-2020 : RESOURCEs and representations For Under-resourced Languages and domains - Gothenburg, Gothenburg, Sweden Duration: 25 Nov 2020 → … https://gu-clasp.github.io/resourceful-2020/

Workshop

Workshop	RESOURCEFUL-2020
Location	Gothenburg
Country/Territory	Sweden
City	Gothenburg
Period	25/11/2020 → …
Internet address	https://gu-clasp.github.io/resourceful-2020/

Keywords

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

Access to Document

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
Project: Other

Cite this

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title = "Creating a Universal Dependencies Treebank of Spoken Frisian-Dutch Code-switched Data",

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 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.",

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author = "Anouck Braggaar and {van der Goot}, Rob",

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TY - ABST

T1 - Creating a Universal Dependencies Treebank of Spoken Frisian-Dutch Code-switched Data

AU - Braggaar, Anouck

AU - van der Goot, Rob

PY - 2021/9/25

Y1 - 2021/9/25

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

Keywords

Access to Document

Fingerprint

Projects

Multi-Task Sequence Labeling Under Adverse Conditions

Cite this