Acoustic DSSS Playback Orchestration for Multi-Device Scene Estimation
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Solution Overview
Problem
Existing audio systems lack efficient methods for estimating acoustic scene metrics, such as audio device audibility and spatial positioning, which are crucial for optimizing audio playback and interaction in complex environments.
Innovation Solution
The implementation of direct sequence spread spectrum (DSSS) signals for audio devices to generate modified playback signals, which are processed and analyzed to estimate acoustic scene metrics like time of flight, audibility, and device location, allowing for optimized audio device coordination and playback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If direct sequence spread spectrum signals are used for acoustic scene metric estimation, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent introduces acoustic DSSS signals as an intermediary carrier to encode and transmit scene metric information. Instead of directly measuring complex acoustic parameters, the system embeds pseudorandom codes in audible signals that serve as intermediaries, making the measurement process more precise while managing complexity through standardized signal processing techniques
Solution Approach 2:
The system changes the parameter representation by encoding scene metrics into temporal patterns of acoustic DSSS signals rather than direct measurements. By modulating presence/absence and timing of coded signals, the system achieves high measurement precision through parameter encoding rather than complex direct sensing
2Productivity
If multiple audio devices play back simultaneously, then productivity is improved, but loss of information increases due to signal interference
Solution Approach 1:
The patent segments the acoustic space by assigning different pseudorandom codes to different audio devices. This code-domain segmentation allows simultaneous playback while maintaining distinguishability, as each device's DSSS signal can be independently correlated and identified despite temporal overlaps
Solution Approach 2:
The system transitions from time-domain signal separation to code-domain separation by embedding unique pseudorandom sequences in each device's playback signal. This dimensional shift from temporal to code-based identification enables simultaneous operation without information loss, as signals are distinguished by their unique code signatures rather than timing
3Reliability
If acoustic DSSS signals are embedded in audio playback, then reliability is improved for metric estimation, but object-generated harmful factors increase due to perceptible artifacts
Solution Approach 1:
The system changes the amplitude parameter of the DSSS signals to be at or below the threshold of human perception. By carefully controlling signal level parameters and using spread spectrum's inherent processing gain, the system achieves reliable metric estimation while keeping audible artifacts minimal or imperceptible
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
Enhances audio device coordination and playback by accurately estimating acoustic scene metrics, improving spatial audio reproduction and voice interaction in multi-device environments.
Implementation Method 1
causing the first audio device to play back the first modified audio playback signals, to generate first audio device playback sound
Data Source
AI summary
Some methods may involve receiving a first content stream that includes first audio signals, rendering the first audio signals to produce first audio playback signals, generating first direct sequence spread spectrum (DSSS) signals, generating first modified audio playback signals by inserting the first DSSS signals into the first audio playback signals, and causing a loudspeaker system to play back the first modified audio playback signals, to generate first audio device playback sound. The method(s) may involve receiving microphone signals corresponding to at least the first audio device playback sound and to second through Nth audio device playback sound corresponding to second through Nth modified audio playback signals (including second through Nth DSSS signals) played back by second through Nth audio devices, extracting second through Nth DSSS signals from the microphone signals and estimating at least one acoustic scene metric based, at least partly, on the second through Nth DSSS signals.