Audio Signature Recognition on Resource-Constrained Devices

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Solution Overview

Problem

Resource-constrained devices struggle to accurately identify advertisements and other content in live television broadcasts due to limitations in processing power and the unpredictable nature of live broadcasting, making it difficult for content distributors to enhance viewer experiences.

Innovation Solution

A system that generates audio signatures using resource-constrained devices, which are then analyzed by a centralized server to identify content, allowing for real-time recognition and enhancement of media streams, including advertisements, by comparing frequency-amplitude pairs to known signatures stored in a database.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If resource-intensive computing techniques are used for signal recognition, then content identification accuracy is improved, but device resource consumption increases making real-time processing impossible on constrained devices

Engineering Contradiction:

Improvecontent identification accuracyVSAvoiddevice processing power consumption

Core Design Contradiction:

Measurement precisionVSUse of energy by moving object

Solution Approach 1:

The patent extracts only the essential acoustic features needed for content identification, ignoring non-critical audio data. This selective extraction enables accurate content recognition while minimizing processing requirements on resource-constrained devices, resolving the contradiction between identification accuracy and energy consumption.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The system performs preliminary processing of audio signals by pre-computing acoustic features and creating simplified representations before transmission to centralized servers. This preliminary action reduces the computational burden on resource-constrained devices while maintaining identification accuracy, as the heavy processing is shifted to servers with greater resources.

Inventive Principle:

Principle #10Preliminary action

2Adaptability or versatility

If complex signal recognition algorithms are implemented on resource-constrained devices, then content identification capability is improved, but device complexity and cost increase

Engineering Contradiction:

Improvecontent identification capabilityVSAvoidprocessing architecture complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent segments the signal recognition system into two parts: a simplified client-side component that extracts basic acoustic features, and a server-side component that performs complex analysis and maintains databases. This segmentation enables content identification capability while keeping individual device complexity low, as the complex algorithms reside on servers rather than on constrained client devices.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent introduces an intermediary communication layer between resource-constrained devices and centralized servers. The devices send simplified acoustic feature data through this intermediary layer, which then routes requests to appropriate server resources. This intermediary approach enables sophisticated content identification without requiring complex local processing architectures.

Inventive Principle:

Principle #24Intermediary (Mediator)

3Productivity

If real-time content identification is achieved using simplified methods, then processing speed is improved, but identification accuracy may deteriorate

Engineering Contradiction:

Improvecontent processing speedVSAvoidcontent identification accuracy

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The system performs preliminary extraction of discriminative acoustic features at the client device, preparing optimized data for rapid transmission. This preliminary action enables real-time processing speed while maintaining accuracy, as the most informative features are extracted beforehand and sent to servers for final identification, avoiding the need to transmit and process entire audio streams.

Inventive Principle:

Principle #10Preliminary action

Applied Scientific Principles

This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.

Function Achieved in This Case

Enables reliable and rapid identification of broadcast content, enabling actions such as supplementing advertisements with links or adjusting playback settings, improving viewer experiences and enhancing content management systems.

Implementation Method 1

A discrete Fourier transform (DFT) is applied to the tapered amplitudes to generate outputs associated with frequency bins

Methodology Applied

Scientific EffectDiscrete Fourier Transform:

Data Source

PatentUS20250016388A1Media signature recognition with resource constrained devices

Publication Date: 2025.01.09 SLING TV LLC

AI summary

The present invention recognizes media content using signatures generated by network devices with limited processing power. An audio signal is prepared for application of a discrete Fourier transform (DFT). Outputs from the DFT include real components and imaginary components that are used to calculate output magnitudes associated with frequency bins. The frequency-amplitude pairs include the output magnitudes and the associated frequency bins. A signature of the audio signal is generated by selecting a predetermined number of frequency-amplitude pairs having dominant output magnitudes. The network devices that generate the signatures may transmit the signatures to a server for analysis. The server may trigger actions in response to detecting known content based on the received signatures matching known signatures.