A beginner's guide to the Zeta-Editing model by Lucataco on Replicate

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This is a simplified guide to an AI model called Zeta-Editing maintained by Lucataco. If you like these kinds of analysis, you should join AImodels.fyi or follow us on Twitter.

Model overview

The zeta-editing model is a zero-shot text-based audio editing tool developed by lucataco. It uses a Denoising Diffusion Probabilistic Model (DDPM) to invert an audio signal and edit it based on a text prompt. This approach allows for highly flexible audio editing without the need for laborious manual processing. Similar models created by lucataco include speaker-diarization, whisperspeech-small, xtts-v2, and magnet, which explore different audio processing and generation capabilities.

Model inputs and outputs

The zeta-editing model takes an audio file and a text prompt as inputs, and returns an edited version of the audio file. The text prompt allows the user to describe the desired changes to the audio, such as transforming it to sound like a specific instrument or genre.

Inputs

Audio: The input audio file to be edited.
Prompt: A text description of the desired edits to the audio.
Steps: The number of diffusion steps to use in the generation process, with higher values yielding higher quality results.
T Start: The starting point for the diffusion process, which controls the balance between the original audio and the edited output.
Audio Version: The specific version of the audio model to use for the editing process.
Cfg Scale Src: The source guidance scale for the DDPM inversion.
Cfg Scale Tar: The target guidance scale for the DDPM inversion.
Source Prompt: An optional description of the original audio input.