Semantic Scholar Open Access 2020 932 sitasi

Jukebox: A Generative Model for Music

Prafulla Dhariwal Heewoo Jun Christine Payne Jong Wook Kim Alec Radford +1 lainnya

Lihat Sumber

Abstrak

We introduce Jukebox, a model that generates music with singing in the raw audio domain. We tackle the long context of raw audio using a multi-scale VQ-VAE to compress it to discrete codes, and modeling those using autoregressive Transformers. We show that the combined model at scale can generate high-fidelity and diverse songs with coherence up to multiple minutes. We can condition on artist and genre to steer the musical and vocal style, and on unaligned lyrics to make the singing more controllable. We are releasing thousands of non cherry-picked samples at this https URL, along with model weights and code at this https URL

Topik & Kata Kunci

Engineering Computer Science Mathematics

Penulis (6)

Prafulla Dhariwal

Heewoo Jun

Christine Payne

Jong Wook Kim

Alec Radford

I. Sutskever

Format Sitasi

APA MLA BibTeX

Dhariwal, P., Jun, H., Payne, C., Kim, J.W., Radford, A., Sutskever, I. (2020). Jukebox: A Generative Model for Music. https://www.semanticscholar.org/paper/67dea28495cab71703993d0d52ca4733b9a66077

Akses Cepat

PDF tidak tersedia langsung

Cek di sumber asli →

Lihat di Sumber

Informasi Jurnal

Tahun Terbit: 2020
Bahasa: en
Total Sitasi: 932×
Sumber Database: Semantic Scholar
Akses: Open Access ✓