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music-generation
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Amphion (/æmˈfaɪən/) is a toolkit for Audio, Music, and Speech Generation. Its purpose is to support reproducible research and help junior researchers and engineers get started in the field of audio, music, and speech generation research and development.
Lab Materials for MIT 6.S191: Introduction to Deep Learning
YuE: Open Full-song Music Generation Foundation Model, something similar to Suno.ai but open
An AI for Music Generation
A fundamental toolkit designed for music, song, and audio generation
🧠+🎧 Build your music algorithms and AI models with the next-gen DAW 🔥
AI Audio Datasets (AI-ADS) 🎵, including Speech, Music, and Sound Effects, which can provide training data for Generative AI, AIGC, AI model training, intelligent audio tool development, and audio applications.
MIDI / symbolic music tokenizers for Deep Learning models 🎶
Apply diffusion models using the new Hugging Face diffusers package to synthesize music instead of images.
Resources on Music Generation with Deep Learning
a list of demo websites for automatic music generation research
OpenMusic: SOTA Text-to-music (TTM) Generation
Generate music from the entropy of Linux 🐧🎵
"Pop Music Transformer: Beat-based Modeling and Generation of Expressive Pop Piano Compositions", ACM Multimedia 2020
Train an LSTM to generate piano or violin/piano music.
Implementation of MusicLM, a text to music model published by Google Research, with a few modifications.
ICASSP 2023-2024 Papers: A complete collection of influential and exciting research papers from the ICASSP 2023-24 conferences. Explore the latest advancements in acoustics, speech and signal processing. Code included. Star the repository to support the advancement of audio and signal processing!
A toolkit for symbolic music generation
A complete and open application for automatic backing tracks generation.
A paper and project list about the cutting edge Speech Synthesis, Text-to-Speech (TTS), Singing Voice Synthesis (SVS), Voice Conversion (VC), Singing Voice Conversion (SVC), and related interesting works (such as Music Synthesis, Automatic Music Transcription, Automatic MOS Prediction, SSL-based ASR...etc).