Implementation of MusicLM, a text to music model published by Google Research, with a few modifications.

OpenMusic: SOTA Text-to-music (TTM) Generation

🔥🔥🔥 A curated list of papers on LLMs-based multimodal generation (image, video, 3D and audio).

Mustango: Toward Controllable Text-to-Music Generation

Local windowed attention multi-instrumental music transformer for supervised music generation

This is an open collection of state-of-the-art (SOTA), novel Text to X (X can be everything) methods (papers, codes and datasets).

Codec Does Matter: Exploring the Semantic Shortcoming of Codec for Audio Language Model

SOTA Google's Perceiver-AR Music Transformer Implementation and Model

some generative audio tools for ComfyUI

[SOTA] [92% acc] 786M-8k-44L-32H multi-instrumental music transformer with true full MIDI instruments range, efficient encoding, octo-velocity and outro tokens

Code for Investigating Personalization Methods in Text to Music Generation

Audio Prompt Adapter: Unleashing music editing abilities for text-to-music with lightweight finetuning [ISMIR 2024]

[DEPRECIATED] [PyTorch 2.0] [638M] [85.33% acc] Full-attention multi-instrumental music transformer for supervised music generation, optimized for speed, efficiency, and performance

[Exclusive for GitHub] deep-muse: Advanced Text-to-Music Generator Implementation

Exploring Bark, the Open-Source Text-to-Audio Generative Model

James Skripchuk's code to convert text to midi. I am going to convert this into flask based app. It uses NLTK to read files, then convert to sentences, then words and then turn those words into an awesome pieces of music. Core work is done by James Skripchuk, I just gave the proper interface to his work.

Turn your words into music! Describe a sound (e.g., happy, spooky) and this app generates a short piece based on your text.

Connect your generative AI apps with Suno API in seconds!

Generative AI version of the GeoGuesser game.

This project merges Natural Language Processing with music generation, using NLP techniques to analyze lyrics and guide the creation of music. It employs sentiment analysis, keyword extraction, and topic modeling, along with Genius and Spotify APIs, to generate music that reflects the emotional depth of the lyrics using the MusicGen model.