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Evaluating prose style transfer with the Bible.

Keith Carlson1, Allen Riddell2, Daniel Rockmore1,3,4

  • 1Department of Computer Science, Dartmouth College Hanover, NH 03755, USA.

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|November 27, 2018
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Summary
This summary is machine-generated.

Researchers created a new parallel corpus from Bible versions for prose style transfer. This dataset aids in training and evaluating models for text style modification tasks.

Keywords:
datasetsparaphrase generationstyle transfer

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Area of Science:

  • Natural Language Processing
  • Computational Linguistics

Background:

  • Prose style transfer requires parallel data for training and evaluation, which is currently scarce.
  • Existing methods for style transfer often lack sufficient high-quality, aligned corpora.

Purpose of the Study:

  • To introduce a novel, high-quality parallel corpus for prose style transfer.
  • To provide a standardized dataset for training and evaluating style transfer models.
  • To establish baseline results for future research in the field.

Main Methods:

  • Leveraged multiple public domain versions of the Bible as a source of stylistically distinct, aligned text.
  • Utilized chapter and verse numbers for sentence alignment across different Bible versions.
  • Developed a standardized data split for training, development, and testing.

Main Results:

  • A highly parallel corpus of stylistically varied text was created.
  • Baseline performance metrics (BLEU, PINC) were established using several models trained on the new corpus.
  • The corpus demonstrated suitability for prose style transfer and potentially other NLP tasks.

Conclusions:

  • The Bible offers a unique and valuable resource for creating parallel corpora in Natural Language Processing.
  • The developed corpus addresses the need for high-quality data in prose style transfer.
  • This resource is expected to advance research in style transfer and related natural language processing applications.