Discriminating Between Similar Nordic Languages

René Haas; Leon Derczynski

Discriminating Between Similar Nordic Languages

Publikation: Konference artikel i Proceeding eller bog/rapport kapitel › Konferencebidrag i proceedings › Forskning › peer review

Abstract

Automatic language identification is a challenging problem. Discriminating between closely related languages is especially difficult. This paper presents a machine learning approach for automatic language identification for the Nordic languages, which often suffer miscategorisation by existing state-of-the-art tools. Concretely we will focus on discrimination between six Nordic languages: Danish, Swedish, Norwegian (Nynorsk), Norwegian (Bokmål), Faroese and Icelandic.

Originalsprog	Engelsk
Titel	Proceedings of the Eighth Workshop on NLP for Similar Languages, Varieties and Dialects
Forlag	Association for Computational Linguistics
Publikationsdato	20 apr. 2021
Sider	67–75
Status	Udgivet - 20 apr. 2021

Emneord

Automatic language identification
Nordic languages
Machine learning
Language discrimination
Natal differentiation

Adgang til dokumentet

NordicDSL (1)Accepteret manuskript, 746 KBLicens: CC BY

https://www.aclweb.org/anthology/2021.vardial-1.8/Licens: CC BY

Citationsformater

@inproceedings{9d31bf1454be41ad88a79396a2d681a5,

title = "Discriminating Between Similar Nordic Languages",

abstract = "Automatic language identification is a challenging problem. Discriminating between closely related languages is especially difficult. This paper presents a machine learning approach for automatic language identification for the Nordic languages, which often suffer miscategorisation by existing state-of-the-art tools. Concretely we will focus on discrimination between six Nordic languages: Danish, Swedish, Norwegian (Nynorsk), Norwegian (Bokm{\aa}l), Faroese and Icelandic.",

keywords = "Automatic language identification, Nordic languages, Machine learning, Language discrimination, Natal differentiation, Automatic language identification, Nordic languages, Machine learning, Language discrimination, Natal differentiation",

author = "Ren{\'e} Haas and Leon Derczynski",

year = "2021",

month = apr,

day = "20",

language = "English",

pages = "67–75",

booktitle = "Proceedings of the Eighth Workshop on NLP for Similar Languages, Varieties and Dialects",

publisher = "Association for Computational Linguistics",

address = "United States",

}

TY - GEN

T1 - Discriminating Between Similar Nordic Languages

AU - Haas, René

AU - Derczynski, Leon

PY - 2021/4/20

Y1 - 2021/4/20

N2 - Automatic language identification is a challenging problem. Discriminating between closely related languages is especially difficult. This paper presents a machine learning approach for automatic language identification for the Nordic languages, which often suffer miscategorisation by existing state-of-the-art tools. Concretely we will focus on discrimination between six Nordic languages: Danish, Swedish, Norwegian (Nynorsk), Norwegian (Bokmål), Faroese and Icelandic.

AB - Automatic language identification is a challenging problem. Discriminating between closely related languages is especially difficult. This paper presents a machine learning approach for automatic language identification for the Nordic languages, which often suffer miscategorisation by existing state-of-the-art tools. Concretely we will focus on discrimination between six Nordic languages: Danish, Swedish, Norwegian (Nynorsk), Norwegian (Bokmål), Faroese and Icelandic.

KW - Automatic language identification

KW - Nordic languages

KW - Machine learning

KW - Language discrimination

KW - Natal differentiation

KW - Automatic language identification

KW - Nordic languages

KW - Machine learning

KW - Language discrimination

KW - Natal differentiation

M3 - Article in proceedings

SP - 67

EP - 75

BT - Proceedings of the Eighth Workshop on NLP for Similar Languages, Varieties and Dialects

PB - Association for Computational Linguistics

ER -

Discriminating Between Similar Nordic Languages

Abstract

Emneord

Adgang til dokumentet

Fingeraftryk

Citationsformater