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Multilingual Persuasion Detection: Video Games as an Invaluable Data Source for NLP

2022-07-10 · Teemu Pöyhönen, Mika Hämäläinen, Khalid Alnajjar

Role-playing games (RPGs) have a considerable amount of text in video game dialogues. Quite often this text is semi-annotated by the game developers. In this paper, we extract a multilingual dataset of persuasive dialogue from several RPGs. We show the viability of this data in building a persuasion detection system using a natural language processing (NLP) model called BERT. We believe that video games have a lot of unused potential as a datasource for a variety of NLP tasks. The code and data described in this paper are available on Zenodo.

📄 PDF Abstract BibTeX arXiv:2207.04453

Code (1)

Teemursu/multilingual_persuasion_dataset 공식 구현

Methods 이 논문이 사용한 방법론

Attention 설명 없음
Linear Layer A Linear Layer is a projection $\mathbf{XW + b}$.
Attention Dropout Attention Dropout is a type of dropout used in attention-based architectures, where elements are randomly dropped out of the…
Layer Normalization Unlike batch normalization, Layer Normalization directly estimates the normalization statistics from the summed inputs…
Linear Warmup With Linear Decay Linear Warmup With Linear Decay is a learning rate schedule in which we increase the learning rate linearly for $n$ updates and then linearly decay afterwards.
Adam 설명 없음
Weight Decay 설명 없음
WordPiece 설명 없음

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