Unsupervised Learning of Cross-Lingual Symbol Embeddings Without Parallel Data

Granroth-Wilding, Mark; Toivonen, Hannu

doi:10.7275/wx64-ea83

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2019

DOI: 10.7275/wx64-ea83

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Unsupervised Learning of Cross-Lingual Symbol Embeddings Without Parallel Data

Mark Granroth-Wilding

Hannu Toivonen

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2019

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Cited by 1 publication

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Cross-Family Similarity Learning for Cognate Identification in Low-Resource Languages

Soisalon-Soininen¹,

Granroth-Wilding²

2019

Proceedings - Natural Language Processing in a Deep Learning World

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We address the problem of cognate identification across vocabularies of any pair of languages. In particular, we focus on the case where the examined languages are low-resource, to the extent that no training data whatsoever in these languages, or even closely related ones, is available for the task. We investigate the extent to which training data from another, unrelated language family can be used instead. Our approach consists of learning a similarity metric from example cognates in Indo-European languages and applying it to low-resource Sami languages of the Uralic family. We apply two models, following previous work: a Siamese convolutional neural network (S-CNN) and a support vector machine (SVM), and compare them with a Levenshtein distance baseline. We test performance on three Sami languages and find that the S-CNN outperforms the other approaches, suggesting that it is better able to learn such general characteristics of cognateness that carry over across language families. We also experiment with fine-tuning the S-CNN model with data from within the language family in order to quantify how well this model can make use of a small amount of target-domain data to adapt.

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Cross-Family Similarity Learning for Cognate Identification in Low-Resource Languages

Soisalon-Soininen¹,

Granroth-Wilding²

2019

Proceedings - Natural Language Processing in a Deep Learning World

Self Cite

View full text Add to dashboard Cite

show abstract

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Unsupervised Learning of Cross-Lingual Symbol Embeddings Without Parallel Data

Cited by 1 publication

References 16 publications

Cross-Family Similarity Learning for Cognate Identification in Low-Resource Languages

Cross-Family Similarity Learning for Cognate Identification in Low-Resource Languages

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