Encoder-decoder model for interactive free verse generation with controllable high-quality rhyming

Paper Title:

Encoder-Decoder Framework for Interactive Free Verses with Generation with Controllable High-Quality Rhyming

Published on:

8 May 2024

Primary Category:

Computation and Language

Paper Authors:

Tommaso Pasini,

Alejo López-Ávila,

Husam Quteineh,

Gerasimos Lampouras,

Jinhua Du,

Yubing Wang,

Ze Li,

Yusen Sun

Bullets

Key Details

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Proposes novel fine-tuning approach for controllable, high-quality rhyming generation

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Prepends rhyming word to start of each line to make critical rhyming decision first

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Generates verses left-to-right for better readability compared to reverse language modeling

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Extensive experiments demonstrate approach produces better rhyming and more readable text

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Introduces high-quality multilingual dataset spanning 13 languages

Explore the topics in this paper

controllable text generation

fine tuning models

lyric generation

poetry generation

rhyme scheme control

AI generated summary

Encoder-decoder model for interactive free verse generation with controllable high-quality rhyming

The paper proposes a novel fine-tuning approach to generate lyrics and free verse poems with controllable, high-quality rhyming. By prepending the rhyming word to the start of each line, the model makes the critical rhyming decision first while still generating the verse left-to-right. Extensive experiments show this approach produces more readable text and better rhyming compared to prior state-of-the-art methods. A high-quality multilingual dataset is also introduced to demonstrate wide applicability.