Audio-Based Device Locationing via Acoustic Fingerprinting
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Solution Overview
Problem
Existing natural language processing systems face challenges in automatically determining the location of devices within an environment to effectively respond to user inputs, leading to inefficiencies in resource allocation and user experience, as users often need to manually specify which device should perform tasks like playing video or music.
Innovation Solution
A system that uses acoustic fingerprinting and watermark encoding to identify devices through speech recognition, allowing devices to output location-specific audio signals that other devices can detect, enabling the system to determine the best device for responding to user requests without user intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If acoustic fingerprinting and watermark encoding are used to enable automatic device locationing, then device identification accuracy is improved, but system complexity increases
Solution Approach 1:
The system performs preliminary actions by having devices output acoustic fingerprint signals and watermarks during initialization and registration phases. These pre-established acoustic signatures enable automatic locationing without requiring complex real-time processing during operation, thus improving identification accuracy while managing system complexity.
Solution Approach 2:
The patent introduces acoustic fingerprint signals and watermarks as intermediary elements that mediate between devices. These intermediaries carry location information through audio channels, enabling indirect device identification and locationing without requiring direct complex communication protocols between devices.
2Ease of operation
If the system automatically determines device location using audio signals, then user burden is reduced, but energy consumption increases
Solution Approach 1:
Devices output acoustic fingerprint signals and watermarks periodically or at specific trigger events (e.g., when a user requests device locationing). This periodic action approach reduces continuous energy consumption while still enabling automatic device identification and locationing when needed, thus reducing user burden without excessive energy waste.
3Measurement precision
If multiple devices output location-specific audio signals continuously, then device locationing accuracy is improved, but audio interference increases
Solution Approach 1:
Each device outputs location-specific audio signals with unique local qualities (distinct acoustic fingerprints and watermarks tailored to its specific location and characteristics). This local quality differentiation enables accurate device identification while the uniqueness of each signal reduces interference from other devices, as each device's acoustic signature is distinct and identifiable.
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
This approach enhances user experience by automatically selecting the appropriate device for tasks, such as playing video or music, based on device capabilities, reducing user burden and improving resource allocation efficiency.
Implementation Method 1
a first device outputs an acoustic fingerprint signal; a second device receives the acoustic fingerprint signal
Implementation Method 2
determine, based on the acoustic fingerprint signal, a location of the first device with respect to the second device
Data Source
AI summary
Techniques for performing audio-based device location determinations are described. A system may send, to a first device, a command to output audio requesting a location of the first device be determined. A second device may receive the audio and send, to the system, data representing the second device received the audio, where the received data includes spectral energy data representing a spectral energy of the audio as received by the second device. The system may, using the spectral energy data, determine attenuation data representing an attenuation experienced by the audio as it traveled from the first device to the second device. The system may generate, based on the attenuation data, spatial relationship data representing a spatial relationship between the first device and the second device, where the spatial relationship data is usable to determine a device for outputting a response to a subsequently received user input.