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Found 7 papers, 2 papers with code
Modeling the Rhythm from Lyrics for Melody Generation of Pop Song
Experiments for Chinese lyric-to-melody generation show that the proposed framework is able to model key characteristics of rhythm and pitch distributions in the dataset, and in a subjective evaluation, the melodies generated by our system were rated as similar to or better than those of a state-of-the-art alternative.
To catch a chorus, verse, intro, or anything else: Analyzing a song with structural functions
Conventional music structure analysis algorithms aim to divide a song into segments and to group them with abstract labels (e. g., 'A', 'B', and 'C').
Supervised Metric Learning for Music Structure Features
Music structure analysis (MSA) methods traditionally search for musically meaningful patterns in audio: homogeneity, repetition, novelty, and segment-length regularity.
Supervised Chorus Detection for Popular Music Using Convolutional Neural Network and Multi-task Learning
This paper presents a novel supervised approach to detecting the chorus segments in popular music.
Modeling the Compatibility of Stem Tracks to Generate Music Mashups
A music mashup combines audio elements from two or more songs to create a new work.
The Freesound Loop Dataset and Annotation Tool
We present the Freesound Loop Dataset (FSLD), a new large-scale dataset of music loops annotated by experts.
Audio and Speech Processing Sound
Neural Loop Combiner: Neural Network Models for Assessing the Compatibility of Loops
Music producers who use loops may have access to thousands in loop libraries, but finding ones that are compatible is a time-consuming process; we hope to reduce this burden with automation.
