Automatic Prediction of Cognate Orthography Using Support Vector Machines

Automatic Prediction of Cognate Orthography Using Support Vector Machines

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by Andrea Mulloni

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@MISC{Mulloni_automaticprediction,
    author = {Andrea Mulloni},
    title = {Automatic Prediction of Cognate Orthography Using Support Vector Machines},
    year = {}
}

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Abstract

This paper describes an algorithm to automatically generate a list of cognates in a target language by means of Support Vector Machines. While Levenshtein distance was used to align the training file, no knowledge repository other than an initial list of cognates used for training purposes was input into the algorithm. Evaluation was set up in a cognate production scenario which mimed a reallife situation where no word lists were available in the target language, delivering the ideal environment to test the feasibility of a more ambitious project that will involve language portability. An overall improvement of 50.58 % over the baseline showed promising horizons. 1

Keyphrases

automatic prediction target language support vector machine cognate production scenario initial list ambitious project overall improvement ideal environment training purpose training file levenshtein distance language portability reallife situation promising horizon