@inproceedings{hartwig-etal-2023-identification,
title = "Identification of Dialect for Eastern and {S}outhwestern {O}jibwe Words Using a Small Corpus",
author = "Hartwig, Kalvin and
Lucas, Evan and
Havens, Timothy",
editor = "Mager, Manuel and
Ebrahimi, Abteen and
Oncevay, Arturo and
Rice, Enora and
Rijhwani, Shruti and
Palmer, Alexis and
Kann, Katharina",
booktitle = "Proceedings of the Workshop on Natural Language Processing for Indigenous Languages of the Americas (AmericasNLP)",
month = jul,
year = "2023",
address = "Toronto, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.americasnlp-1.8",
doi = "10.18653/v1/2023.americasnlp-1.8",
pages = "58--66",
abstract = "The Ojibwe language has several dialects that vary to some degree in both spoken and written form. We present a method of using support vector machines to classify two different dialects (Eastern and Southwestern Ojibwe) using a very small corpus of text. Classification accuracy at the sentence level is 90{\%} across a five-fold cross validation and 72{\%} when the sentence-trained model is applied to a data set of individual words. Our code and the word level data set are released openly on Github at [link to be inserted for final version, working demonstration notebook uploaded with paper].",
}
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%0 Conference Proceedings
%T Identification of Dialect for Eastern and Southwestern Ojibwe Words Using a Small Corpus
%A Hartwig, Kalvin
%A Lucas, Evan
%A Havens, Timothy
%Y Mager, Manuel
%Y Ebrahimi, Abteen
%Y Oncevay, Arturo
%Y Rice, Enora
%Y Rijhwani, Shruti
%Y Palmer, Alexis
%Y Kann, Katharina
%S Proceedings of the Workshop on Natural Language Processing for Indigenous Languages of the Americas (AmericasNLP)
%D 2023
%8 July
%I Association for Computational Linguistics
%C Toronto, Canada
%F hartwig-etal-2023-identification
%X The Ojibwe language has several dialects that vary to some degree in both spoken and written form. We present a method of using support vector machines to classify two different dialects (Eastern and Southwestern Ojibwe) using a very small corpus of text. Classification accuracy at the sentence level is 90% across a five-fold cross validation and 72% when the sentence-trained model is applied to a data set of individual words. Our code and the word level data set are released openly on Github at [link to be inserted for final version, working demonstration notebook uploaded with paper].
%R 10.18653/v1/2023.americasnlp-1.8
%U https://aclanthology.org/2023.americasnlp-1.8
%U https://doi.org/10.18653/v1/2023.americasnlp-1.8
%P 58-66
Markdown (Informal)
[Identification of Dialect for Eastern and Southwestern Ojibwe Words Using a Small Corpus](https://aclanthology.org/2023.americasnlp-1.8) (Hartwig et al., AmericasNLP 2023)
ACL