AI Audio Separation for In-Vehicle Surround Sound Mixing

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Solution Overview

Problem

Existing in-vehicle surround sound systems face limitations in immersive experience due to insufficient multi-channel sound source content and suboptimal upmixing technologies, leading to poor tone quality and limited music detail adjustment.

Innovation Solution

A computer-program product and in-vehicle sound device that utilize an AI audio separation model and sound mixing algorithms to customize multi-channel surround sound conversion parameters, simulating a real surround sound space effect by extracting features, separating audio signals, and optimizing equalization and mixing parameters for enhanced immersive experiences.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Area of stationary object

If traditional upmixing technology (stereo flipping and subtraction) is used, then the system can create a broader sound field, but the tone quality is lost and the effect is poor

Engineering Contradiction:

Improvesound field coverageVSAvoidtone quality

Core Design Contradiction:

Area of stationary objectVSManufacturing precision

Solution Approach 1:

The patent changes the fundamental parameters of audio processing by replacing traditional upmixing algorithms with AI-based deep learning models. The system uses neural networks to learn optimal mappings from stereo to multi-channel audio, transforming the mathematical operations from simple signal manipulation to intelligent pattern recognition and synthesis, thereby achieving both broad sound field coverage and high tone quality

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The patent substitutes the mechanical/mathematical upmixing process with an AI-based computational system. Instead of using fixed algorithms like stereo flipping and subtraction, the system employs deep learning models that have been trained on extensive audio datasets, replacing rigid mathematical operations with adaptive neural network inference to achieve superior audio quality

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Productivity

If traditional upmixing technology is used, then the system can process audio signals, but the music detail adjustment is limited and professional multi-channel processing is required

Engineering Contradiction:

Improveaudio processing capabilityVSAvoidmusic detail adjustment

Core Design Contradiction:

ProductivityVSAdaptability or versatility

Solution Approach 1:

The patent implements a universal audio processing system where a single AI-based platform can handle multiple audio formats and scenarios. The deep learning model is trained to process various types of audio content (music, podcasts, movies) and can adapt to different multi-channel configurations (5.1, 7.1, Dolby Atmos), eliminating the need for separate professional processing systems for each use case

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The patent introduces dynamic adaptability through AI models that can adjust processing parameters in real-time based on the input audio characteristics. The system dynamically analyzes the audio signal and automatically optimizes mixing parameters, equalization, and spatial positioning, allowing flexible music detail adjustment without requiring manual configuration or professional equipment

Inventive Principle:

Principle #15Dynamics

3Ease of operation

If insufficient multi-channel sound source content is provided, then the system can still process audio, but the immersive experience is poor

Engineering Contradiction:

Improveaudio processingVSAvoidimmersive experience

Core Design Contradiction:

Ease of operationVSReliability

Solution Approach 1:

The patent performs preliminary training of the AI model using extensive multi-channel audio datasets and virtual acoustic environment simulations before actual use. The system pre-learning optimal audio rendering techniques and spatial positioning algorithms, so that when processing actual audio content, it can immediately generate high-quality immersive sound fields without requiring extensive real-time computation or specialized content

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS20250324218A1Computer readable medium and in-vehicle sound device for converting in-vehicle audio into surround sound

Publication Date: 2025.10.16 TAN BO

AI summary

A non-transitory computer readable medium and an in-vehicle sound device relating to convert a vehicle audio into a surround sound and a sound system are provided. The non-transitory computer readable medium stores a computer-program product includes instructions for extracting features of an audio data for debugging based on a vehicle audio signal; performing classification according to the extracted features to separate the audio data into a plurality of single audio signals; mixing the plurality of separated single audio signals, and recording parameters of the current sound mixing algorithm as original sound mixing parameters; pre-configuring a plurality of spatial reverberation modes; debugging the original sound mixing parameters; and determining and saving optimized audio channel equalization parameters and optimized sound mixing parameters corresponding to the spatial reverberation modes as the multi-channel surround sound conversion parameters.