Multi-Conditioned Audio Generation for Precise Feature Control
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Solution Overview
Problem
Existing text-to-audio generation systems lack the flexibility to control specific features of generated audio beyond a text prompt, limiting user control over audio characteristics.
Innovation Solution
A multi-conditioned latent diffusion model is employed to generate audio using both audio input and style conditions, allowing for precise manipulation of audio characteristics through local and global control adapters, incorporating text embeddings and audio embeddings to define desired audio outputs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If text-to-audio generation systems use only text prompts to generate audio, then the system is simple to operate, but the user cannot control specific features of the generated audio
Solution Approach 1:
The patent segments the control parameters into different types: text prompts for high-level audio characteristics and audio condition inputs for specific feature control. This segmentation allows users to control specific audio features without complicating the overall system operation, as each control type serves a distinct purpose and can be independently adjusted.
Solution Approach 2:
The patent introduces audio condition inputs as intermediaries between the user's control intentions and the audio generation process. These condition inputs act as mediators that translate user specifications into precise control signals for the diffusion model, enabling fine-grained control of audio features while maintaining ease of use through a structured interface.
2Manufacturing precision
If the system uses multiple conditions (audio input and style conditions) for generation, then the audio feature control is precise, but the device complexity increases
Solution Approach 1:
The patent segments the complex generation process into distinct modules: text prompt processing, audio condition extraction, style condition extraction, and diffusion model generation. Each module handles a specific aspect of control, making the overall system more manageable and easier to implement despite the multiple conditions involved.
Solution Approach 2:
The patent designs the system to handle multiple types of inputs (text prompts, audio conditions, style conditions) through a unified diffusion model framework. This multi-functionality allows the same core model to process different input types and generate varied audio outputs, reducing the need for separate specialized systems for each control mode.
Data Source
AI summary
A method for audio generation includes defining an audio input condition for an obtained input using an encoder, where the obtained input is indicative of one or more audio characteristics. The method further includes defining an audio style condition of a selected audio style profile employing an audio feature extraction neural network, and outputting a generated audio data indicative of a desired generated audio using a multi-conditioned latent diffusion model that employs the audio input condition and the audio style condition as adapters to the multi-conditioned latent diffusion model.