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Found 10 papers, 2 papers with code
A Melody-Conditioned Lyrics Language Model
This paper presents a novel, data-driven language model that produces entire lyrics for a given input melody.
Self-Supervised Contrastive Learning for Singing Voices
To acquire robust representations in an unsupervised manner, regular self-supervised contrastive learning trains neural networks to make the feature representation of a sample close to those of its computationally transformed versions.
Unsupervised Learning of Style-sensitive Word Vectors
This paper presents the first study aimed at capturing stylistic similarity between words in an unsupervised manner.
Modeling Discourse Segments in Lyrics Using Repeated Patterns
This study proposes a computational model of the discourse segments in lyrics to understand and to model the structure of lyrics.
Semi-supervised Learning with Multi-Domain Sentiment Word Embeddings
Word embeddings are known to boost performance of many NLP tasks such as text classification, meanwhile they can be enhanced by labels at the document level to capture nuanced meaning such as sentiment and topic.
A Computational Evaluation Framework for Singable Lyric Translation
Lyric translation plays a pivotal role in amplifying the global resonance of music, bridging cultural divides, and fostering universal connections.
