most citedOf All StrIPEs: Investigating Structure-informed Positional Encoding for Efficient Music Generation

1 citations · 1 across the 3 of their papers we have counts for

collaborators

5 papers

eess.AS2025

Melody-Lyrics Matching with Contrastive Alignment Loss

Changhong Wang, Michel Olvera, Gaël Richard

The connection between music and lyrics is far beyond semantic bonds. Conceptual pairs in the two modalities such as rhythm and rhyme, note duration and syllabic stress, and struct…

cs.SD2025★ 1 cited

Of All StrIPEs: Investigating Structure-informed Positional Encoding for Efficient Music Generation

Manvi Agarwal, Changhong Wang, Gael Richard

While music remains a challenging domain for generative models like Transformers, a two-pronged approach has recently proved successful: inserting musically-relevant structural inf…

cs.SD2025

F-StrIPE: Fast Structure-Informed Positional Encoding for Symbolic Music Generation

Manvi Agarwal, Changhong Wang, Gael Richard

While music remains a challenging domain for generative models like Transformers, recent progress has been made by exploiting suitable musically-informed priors. One technique to l…

cs.LG2025

Investigating the Sensitivity of Pre-trained Audio Embeddings to Common Effects

Victor Deng, Changhong Wang, Gael Richard +1

In recent years, foundation models have significantly advanced data-driven systems across various domains. Yet, their underlying properties, especially when functioning as feature…

cs.SD2024

Structure-informed Positional Encoding for Music Generation

Manvi Agarwal, Changhong Wang, Gaël Richard

Music generated by deep learning methods often suffers from a lack of coherence and long-term organization. Yet, multi-scale hierarchical structure is a distinctive feature of musi…