Starved neural learning : Morpheme segmentation using low amounts of data

Starved neural learning : Morpheme segmentation using low amounts of data

Automatic morpheme segmentation as a field has been dominated by unsupervised methods since its inception. Partly due to theoretical motivations, but also due to resource constraints. Given the success neural network methods have shown on a wide variety of field in later years, it would seem compell...

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Bibliographic Details
Main Author: Persson, Peter
Format: Others
Language:English
Published: Stockholms universitet, Avdelningen för datorlingvistik 2018
Subjects:
morpheme segmentation
machine learning
neural networks
convolutional neural networks
LSTM
General Language Studies and Linguistics
Jämförande språkvetenskap och allmän lingvistik
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-160953

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http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-160953

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