How can generative adversarial networks impact computer generated art? Insights from poetry to melody conversion - ScienceDirect
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Guide to sound engines
ASAP: A DATASET OF ALIGNED SCORES AND PERFORMANCES FOR PIANO TRANSCRIPTION
GitHub - itec-hust/OMAPS: The OMAPS (Ordinary MIDI Aligned Piano Sounds) dataset was recorded from Yamaha electric piano P115 to evaluate audio-visual fusion piano transcription models.
ASAP: A DATASET OF ALIGNED SCORES AND PERFORMANCES FOR PIANO TRANSCRIPTION
A Comprehensive Survey on Deep Music Generation: Multi-level Representations, Algorithms, Evaluations, and Future Directions
The MAESTRO Dataset
The Maestro Dataset v2 | Kaggle
ENABLING FACTORIZED PIANO MUSIC MODELING AND GENERATION WITH THE MAESTRO DATASET
MusicallyAI | Devpost
ASAP: A DATASET OF ALIGNED SCORES AND PERFORMANCES FOR PIANO TRANSCRIPTION
Transition-Aware: A More Robust Approach for Piano Transcription
Visualizing Musical Performance. As a musician and a data scientist, I… | by D. Ryan Miller | Towards Data Science
Writing a music album with Deep Learning | by Nicolás Schmidt | Towards Data Science
Example of the effect of the interaction of crescendo after a... | Download Scientific Diagram
ASAP: A DATASET OF ALIGNED SCORES AND PERFORMANCES FOR PIANO TRANSCRIPTION
The Maestro Dataset v2 | Kaggle
Google created an AI-powered piano version of Guitar Hero
Real-time error correction and performance aid for MIDI instruments arXiv:2011.13122v1 [cs.SD] 26 Nov 2020
Deep Learning for Expressive Piano Performances | Popgun Labs
Performance RNN: Generating Music with Expressive Timing and Dynamics
MusicallyAI | Devpost
The MAESTRO Dataset and Wave2Midi2Wave
