28 citations · 73 across the 11 of their papers we have counts for
11 papers
Motif-Centric Representation Learning for Symbolic Music
Yuxuan Wu, Roger B. Dannenberg, Gus Xia
Music motif, as a conceptual building block of composition, is crucial for music structure analysis and automatic composition. While human listeners can identify motifs easily, exi…
On the Effectiveness of Speech Self-supervised Learning for Music
Yinghao Ma, Ruibin Yuan, Yizhi Li +12
Self-supervised learning (SSL) has shown promising results in various speech and natural language processing applications. However, its efficacy in music information retrieval (MIR…
LyricWhiz: Robust Multilingual Zero-shot Lyrics Transcription by Whispering to ChatGPT
Le Zhuo, Ruibin Yuan, Jiahao Pan +10
We introduce LyricWhiz, a robust, multilingual, and zero-shot automatic lyrics transcription method achieving state-of-the-art performance on various lyrics transcription datasets,…
MERT: Acoustic Music Understanding Model with Large-Scale Self-supervised Training
Yizhi Li, Ruibin Yuan, Ge Zhang +17
Self-supervised learning (SSL) has recently emerged as a promising paradigm for training generalisable models on large-scale data in the fields of vision, text, and speech. Althoug…
Relating Human Perception of Musicality to Prediction in a Predictive Coding Model
Nikolas McNeal, Jennifer Huang, Aniekan Umoren +4
We explore the use of a neural network inspired by predictive coding for modeling human music perception. This network was developed based on the computational neuroscience theory…
What is missing in deep music generation? A study of repetition and structure in popular music
Shuqi Dai, Huiran Yu, Roger B. Dannenberg
Structure is one of the most essential aspects of music, and music structure is commonly indicated through repetition. However, the nature of repetition and structure in music is s…