Compact Stem Separation Modules for Resource-Constrained Devices
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Solution Overview
Problem
Conventional stem separation algorithms require significant computational resources and are typically implemented in high-resource environments, making them unsuitable for resource-constrained devices.
Innovation Solution
A compact, lightweight stem separation module is implemented on user electronic devices, utilizing condensed neural processing units and reduced feature sizes to perform stem separation locally, allowing isolation and playback of audio stems in resource-constrained environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional stem separation algorithms are used, then stem separation performance is improved, but computational resource requirements increase
Solution Approach 1:
The patent applies model distillation to create a compressed version of the original stem separation model. The distilled model captures the essential separation capabilities while using significantly fewer computational resources, enabling high-performance stem separation on resource-constrained devices without requiring the full original model.
Solution Approach 2:
The patent transforms the stem separation model by changing its parameter representation through distillation techniques. This creates a new model parameter set that maintains separation accuracy while reducing computational complexity, allowing the system to operate efficiently on mobile and embedded devices.
2Measurement precision
If conventional stem separation algorithms are used, then stem separation performance is improved, but device complexity increases
Solution Approach 1:
The patent creates a simplified copy of the conventional stem separation algorithm through model distillation. This distilled version maintains the core separation functionality while removing complex computational dependencies, making it suitable for deployment on standard mobile devices without requiring specialized high-performance computing hardware.
3Ease of operation
If stem separation is performed locally on user devices, then ease of operation is improved, but computational resource requirements increase
Solution Approach 1:
The patent distills the stem separation model into a compact version that can run locally on user devices. This distilled model maintains separation quality while consuming significantly less power than the original model, enabling convenient local operation on mobile devices without requiring excessive computational resources.
Data Source
AI summary
A method comprises: (i) presenting a user interface frontend that displays a control for activating a system-level stem separation mode; and (ii) after receiving user input activating the system-level stem separation mode, and when a system generates a system output audio signal based on audio associated with one or more applications executing on the system: (a) refraining from sending the system output audio signal to one or more playback devices over a system audio output signal path; (b) identifying a set of one or more segments of the system output audio signal; (c) processing the set of one or more segments using a selected stem separation module to generate a set of stem-separated segments comprising a plurality of audio stems; and (d) sending at least one audio stem from the plurality of audio stems to the one or more playback devices via the system audio output signal path.