14 citations · 34 across the 6 of their papers we have counts for
6 papers
Seed-Music: A Unified Framework for High Quality and Controlled Music Generation
Ye Bai, Haonan Chen, Jitong Chen +35
We introduce Seed-Music, a suite of music generation systems capable of producing high-quality music with fine-grained style control. Our unified framework leverages both auto-regr…
SymPAC: Scalable Symbolic Music Generation With Prompts And Constraints
Haonan Chen, Jordan B. L. Smith, Janne Spijkervet +5
Progress in the task of symbolic music generation may be lagging behind other tasks like audio and text generation, in part because of the scarcity of symbolic training data. In th…
Jointist: Simultaneous Improvement of Multi-instrument Transcription and Music Source Separation via Joint Training
Kin Wai Cheuk, Keunwoo Choi, Qiuqiang Kong +5
In this paper, we introduce Jointist, an instrument-aware multi-instrument framework that is capable of transcribing, recognizing, and separating multiple musical instruments from…
Jointist: Joint Learning for Multi-instrument Transcription and Its Applications
Kin Wai Cheuk, Keunwoo Choi, Qiuqiang Kong +5
In this paper, we introduce Jointist, an instrument-aware multi-instrument framework that is capable of transcribing, recognizing, and separating multiple musical instruments from…
GiantMIDI-Piano: A large-scale MIDI dataset for classical piano music
Qiuqiang Kong, Bochen Li, Jitong Chen +1
Symbolic music datasets are important for music information retrieval and musical analysis. However, there is a lack of large-scale symbolic datasets for classical piano music. In…
High-resolution Piano Transcription with Pedals by Regressing Onset and Offset Times
Qiuqiang Kong, Bochen Li, Xuchen Song +2
Automatic music transcription (AMT) is the task of transcribing audio recordings into symbolic representations. Recently, neural network-based methods have been applied to AMT, and…