AI audio generation

EzAudio is an advanced text-to-audio (T2A) generation model capable of creating high-quality audio from text prompts. It sets a new standard for open source T2A models, providing fast, efficient and realistic sound effect generation.

Stable Audio Open is a technology that generates up to 47 seconds of stereo audio from text prompts. It consists of three main components: an autoencoder that compresses waveforms to manageable sequence lengths, a T5-based text embedding for text conditions, and a diffusion-based transformation (DiT) model that operates in the latent space of the autoencoder. The technology excels at generating audio, capable of generating various types of audio based on text prompts, such as percussion, electronic music, natural sounds, and more.

AudioLCM is a text-to-audio generation model based on PyTorch, which uses a latent consistency model to generate high-quality and efficient audio. This model was developed by Huadai Liu and others, providing an open source implementation and pre-trained model. It can convert text descriptions into near-real audio and has important application value, especially in fields such as speech synthesis and audio production.

MusicGen Stereo is a family of models for generating stereo music, including small, medium, large and melodic large models. These models can convert text into high-quality audio and are suitable for a variety of music generation scenarios. Pricing is based on model size and usage, and is positioned to provide users with high-quality music generation solutions.