haoheliu/AudioLDM

Features

• Latent Diffusion Models - Provides a latent diffusion model that performs iterative denoising within a compressed latent space for efficient audio synthesis.
• Audio Generation Models - Implements a specialized audio generation model for producing high-fidelity sound effects, music, and speech.
• Cross-Attention Mechanisms - Uses cross-attention mechanisms to integrate text embeddings into the diffusion process for guided audio generation.
• Spectrogram Encoders - Transforms audio into spectrogram representations before encoding them into the latent space for processing.
• Variational Autoencoders - Utilizes a variational autoencoder to compress raw audio waveforms into continuous latent distributions for generative tasks.
• Iterative Denoising Pipelines - Employs an iterative denoising pipeline to recover high-fidelity audio signals from Gaussian noise.
• Text-to-Audio Synthesis - Functions as a neural text-to-audio synthesis system converting natural language descriptions into speech, music, and sound effects.
• Audio-to-Audio Synthesis - Creates new audio clips based on existing files to replicate or transform specific acoustic events.
• Audio Style Transfers - Modifies the style of sound files using text prompts while preserving the original audio structure.
• Audio Inpainting And Editing - Enables surgical audio modification and segment regeneration using text-based guidance to fill recording gaps.
• Audio Super-Resolution - Provides audio super-resolution capabilities to increase the sample rate and fidelity of low-quality recordings.

Star history