EGDB-PG:
an extended version of EGDB that comes with 256 amp-rendered tones
EMOPIA+: extended version
of EMOPIA that comes with a functional representation-based tokenization
EMOPIA: a multimodal dataset
comprising audio+MIDI of emotion-annotated pop piano solo pieces
EGDB_BIAS_FX2: the EGDB dataset
rendered with the Positive Grid BIAS FX2 Plugin, published at
DAFx’24
EGDB:
a dataset that contains transcriptions of the electric guitar performance
of 240 tablatures rendered with different tones, published at
ICASSP’22
AILabs.tw Pop1K7: a
dataset comprising 1747 transcribed piano performances of Western,
Japanese and Korean pop songs, compiled in the Compound Word Transformer
paper (AAAI’21)
DadaGP: a dataset of ~26k
GuitarPro songs in ~800 genres, converted to a token sequence format for
generative language models like GPT2, TransformerXL, etc
CCMED & WWMED:
corpora of Western classical music excerpts (WCMED) and Chinese classical
music excerpts (CCMED) annotated with emotional valence and arousal
values (ICASSP’20 paper-a)
#nowplaying-RS:
a new benchmark dataset for building context-aware
music recommender systems
(SMC’18 paper)
Lakh Pianoroll
Dataset
(LPD): a collection of 174,154 unique multi-track piano-rolls derived
from the MIDI files in Lakh MIDI Dataset (LMD), used in our MuseGAN paper
(AAAI’18 paper)
iKala: 252 30-second
excerpts sampled from 206 iKala songs (plus 100 hidden excerpts reserved
for MIREX
SVS 2014-2016) (ICASSP’15 paper)
Su
Dataset for automatic music transcription in piano solo, piano
quintet, string quartet, violin sonata, choir, and symphony
(ISMIR’16 and ISMIR’15 papers)
The
AMG1608 dataset
for personalized
music emotion recognition (ICASSP’15
paper)
The
CH818dataset for music emotion recognition in Chinese Pop songs
The
DEAM and MediaEvaldataset for dynamic and static music
emotion recognition
(used in the ‘Emotion in Music’ Task in MediaEval 2013-2015)
CAL500expDataset
for time-varying music auto-tagging (ICME’14 paper)
CAL10k:
10k songs with 140 genre tags (TMM’13 paper)
LiveJournal:
40k blog articles with user mood labels and music tags (TMM’13
paper)
Codes
MuseControlLite:
Multifunctional music generation with lightweight conditioners
(ICML’25 paper)
METEOR: Melody-aware
Texture-controllable Symbolic Orchestral Music Generation via Transformer
VAE (IJCAI’25 paper)
diffFx: A
PyTorch-based library for differentiable audio effects processing,
enabling deep learning integration with professional audio processing
algorithms(ISMIR-LBD’25 paper)
PyNeuralFx: a Python
package for neural audio effect modeling
EMO-Disentanger:
emotion-driven piano music generation via two-stage disentanglement and
functional representation (ISMIR’24 paper)
EMO_Harmonizer:
early version of
EMO-Disentanger, for emotion-contorllable melody harmonization
MusiConGen: rhythm and
chord control for Transformer-based text-to-music generation(ISMIR’24
paper)
AP-adapter: audio prompt
adapter: unleashing music editing abilities for text-to-music with
lightweight finetuning (ISMIR’24 paper)
PiCoGen2: piano cover
generation with transfer learning approach and weakly aligned data
(ISMIR’24 paper)
Compose &
Embellish: Well-structured piano performance generation via a
two-stage approach (ICASSP’23
paper)
MuseMorphose: a
Transformer-VAE architecture for per-bar music style transfer
Variable-length
piano infilling: a XLNet-based model for inpainting a piano sequence
with variable number of notes (up to 128 notes) (ISMIR’21 paper)
LoopTest: a
benchmark of audio-domain musical phrase generation using drum loops
(ISMIR’21 paper)
drum-aware4beat:
drum-aware ensemble architecture for improved joint musical beat and
downbeat tracking (SPL’21 paper)
CP
Transformer: the world’s first neural sequence model for music
generation at full-song length (AAAI’21 paper)
Pop Music Transformer: a
neural sequence model for beat-based automatic piano music composition
(MM’20 paper)
MIDI toolkit:
Designed for handling MIDI in symbolic timing (ticks), which is the
native format of MIDI timing; we keep the midi parser as simple as
possible, and offer several useful utility functions
Singer-identification-in-artist20:
the convolutional recurrent neural network with melody model for singer
identification with the shuffle-and-remix data augmentation technique
(ICASSP’20 paper-c)
Speech-to-Singing
Conversion:
an end to end model for converting speech voice into singing voice
(ICASSP’20 paper-b)