SongSong: A Time Phonograph for Chinese SongCi Music from Thousand of Years Away

Fuente: arXiv
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Autori principali: Li, Jiajia, Hu, Jiliang, Pan, Ziyi, Chen, Chong, Li, Zuchao, Wang, Ping, Zhang, Lefei
Natura: Preprint
Pubblicazione: 2026
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author Li, Jiajia
Hu, Jiliang
Pan, Ziyi
Chen, Chong
Li, Zuchao
Wang, Ping
Zhang, Lefei
author_facet Li, Jiajia
Hu, Jiliang
Pan, Ziyi
Chen, Chong
Li, Zuchao
Wang, Ping
Zhang, Lefei
contents Recently, there have been significant advancements in music generation. However, existing models primarily focus on creating modern pop songs, making it challenging to produce ancient music with distinct rhythms and styles, such as ancient Chinese SongCi. In this paper, we introduce SongSong, the first music generation model capable of restoring Chinese SongCi to our knowledge. Our model first predicts the melody from the input SongCi, then separately generates the singing voice and accompaniment based on that melody, and finally combines all elements to create the final piece of music. Additionally, to address the lack of ancient music datasets, we create OpenSongSong, a comprehensive dataset of ancient Chinese SongCi music, featuring 29.9 hours of compositions by various renowned SongCi music masters. To assess SongSong's proficiency in performing SongCi, we randomly select 85 SongCi sentences that were not part of the training set for evaluation against SongSong and music generation platforms such as Suno and SkyMusic. The subjective and objective outcomes indicate that our proposed model achieves leading performance in generating high-quality SongCi music.
format Preprint
id arxiv_https___arxiv_org_abs_2602_24071
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle SongSong: A Time Phonograph for Chinese SongCi Music from Thousand of Years Away
Li, Jiajia
Hu, Jiliang
Pan, Ziyi
Chen, Chong
Li, Zuchao
Wang, Ping
Zhang, Lefei
Sound
Computation and Language
Recently, there have been significant advancements in music generation. However, existing models primarily focus on creating modern pop songs, making it challenging to produce ancient music with distinct rhythms and styles, such as ancient Chinese SongCi. In this paper, we introduce SongSong, the first music generation model capable of restoring Chinese SongCi to our knowledge. Our model first predicts the melody from the input SongCi, then separately generates the singing voice and accompaniment based on that melody, and finally combines all elements to create the final piece of music. Additionally, to address the lack of ancient music datasets, we create OpenSongSong, a comprehensive dataset of ancient Chinese SongCi music, featuring 29.9 hours of compositions by various renowned SongCi music masters. To assess SongSong's proficiency in performing SongCi, we randomly select 85 SongCi sentences that were not part of the training set for evaluation against SongSong and music generation platforms such as Suno and SkyMusic. The subjective and objective outcomes indicate that our proposed model achieves leading performance in generating high-quality SongCi music.
title SongSong: A Time Phonograph for Chinese SongCi Music from Thousand of Years Away
topic Sound
Computation and Language
url https://arxiv.org/abs/2602.24071