Papers by Penny Karanasou

2 papers
Selecting Machine-Translated Data for Quick Bootstrapping of a Natural Language Understanding System (N18-3)

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Challenge: In recent years, there has been growing interest in voice-controlled devices, such as Amazon Alexa or Google home.
Approach: They investigate the use of Machine Translation to bootstrap a natural language understanding system for a new language for the use case of a large-scale voice-controlled device.
Outcome: The proposed method reduces the time and cost of getting annotated corpus for a new language while still providing a large enough coverage of user requests.
Cross-lingual Transfer Learning for Japanese Named Entity Recognition (N19-2)

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Challenge: a recent study focuses on bootstrapping named entity models from English to Japanese . TL is a technique that overcomes linguistic differences between the target and source languages .
Approach: They propose to use a deep neural network model to transfer weights between languages . they also propose a novel approach that romanizes a portion of the Japanese input .
Outcome: The proposed approach overcomes linguistic differences by romanizing a portion of the Japanese input.

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