InspireMusicTranslation site

What is InspireMusic

InspireMusic is an AIGC toolkit open-sourced by Alibaba Tongyi Labs that integrates theMusic Generation, song generation, and audio generation capabilities.

InspireMusic Core Functions and Features

1. Music Generation::
   • Supports the rapid generation of music compositions that meet the requirements through simple text descriptions.
   • Covering a wide range of song styles, emotional expressions and complex musical structure control, it offers great creative freedom and flexibility.
2. Audio Generation::
   • Capable of generating high-quality audio compositions, it supports multiple sample rates (e.g. 24kHz and 48kHz).
   • Provides fast mode (fast generation) and high sound quality mode to meet the needs of different users.
3. easy-to-use::
   • An easy-to-use text-generated music/song/audio creation tool for music lovers.
   • Simple model fine-tuning and inference tools provide users with an efficient training and tuning experience.
4. community-driven::
   • An open platform for collaborative innovation for researchers, developers and enthusiasts.
   • Community members are encouraged to participate in the experience and research and development to promote the continuous advancement of music generation technology.

InspireMusic Technology Architecture and Principles

The core architecture of InspireMusic consists of an audio tokenizer, an autoregressive Transformer model, a diffusion model (CFM), and a Vocoder.These components work together to enable music generation:

1. Audio Tokenizer::
   • The input continuous audio features are converted into discrete audio tokens using a single codebook WavTokenizer with a high compression ratio.
   • Transform audio data into a form that the model can handle.
2. Autoregressive Transformer Model::
   • Autoregressive Transformer model initialized based on Qwen model for predicting audio tokens based on textual cues.
   • The model is able to understand textual descriptions and generate music sequences that match them.
3. Diffusion modeling (CFM)::
   • Reconstructing the latent features of audio using a diffusion model based on ordinary differential equations.
   • The CFM model recovers high-quality audio features from the generated audio tokens, enhancing the coherence and naturalness of the music.
4. Vocoder::
   • The reconstructed audio features are converted into high-quality audio waveforms to output the final musical composition.

InspireMusic Application Scenarios and Uses

1. music composition::
   • Providing music creators with innovative soundscapes and empowering music creation.
   • Supports the generation of multiple styles of musical compositions via text or audio cues.
2. audio processing::
   • In the field of audio processing, InspireMusic generates high-quality audio productions that meet the needs of professional users.
3. Individual music lovers::
   • An easy-to-use music generation tool for individual music lovers to create their own music compositions.

InspireMusic User Guide and Resources

1. code repository::
   • Users can download code libraries, installation guides, pre-trained models, and other resources from this repository.
2. Installation steps::
   • Clone the repository and update the submodules.
   • Create and activate a Python 3.8 environment.
   • Install the necessary dependencies, including pynini, the packages in requirements.txt, and flash-attn.
   • Download the pre-trained model.
3. Online Demo::
   • Users can experience InspireMusic's features through an online demo address.
4. basic usage::
   • Provides sample scripts for training LLM and flow matching models as well as inference scripts.
   • The user can train the model and generate music according to the provided scripts.

Open source repository address:https://github.com/FunAudioLLM/InspireMusic
Demo Address:https://huggingface.co/spaces/FunAudioLLM/InspireMusic