Papers by Kento Watanabe

3 papers
A Melody-Conditioned Lyrics Language Model (N18-1)

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Challenge: Existing models for lyrics generation are insufficient to capture relationship between lyrics and melody.
Approach: They propose a data-driven language model that generates entire lyrics for a given melody.
Outcome: The proposed model generates fluent lyrics while maintaining compatibility between lyrics and melodies.
Unsupervised Learning of Style-sensitive Word Vectors (P18-2)

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Challenge: Existing studies on what is said and how it is said focus on stylistic variations . lack of objective definitions is a major difficulty in studying style .
Approach: They propose to extend the continuous bag of words embedding model to learn style-sensitive word vectors using a wider context window.
Outcome: The proposed extensions contribute to the acquisition of style-sensitive word embeddings.
A Data-Driven Method for Analyzing and Quantifying Lyrics-Dance Motion Relationships (2025.naacl-long)

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Challenge: Existing studies have not explored the relationships between lyrics and dance motions . previous studies focused on synthesizing or retrieving dance motion from lyrics .
Approach: They propose a method to detect parts of songs where meaningful relationships exist . they use clustering to transform lyrics and dance motions into symbols .
Outcome: The proposed method outperforms existing methods on prose and non-dance dance motions.

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