Multi-modal Audio Processing for Voice Recognition
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Solution Overview
Problem
Current voice-controlled devices struggle with accurately recognizing voice commands in noisy environments due to interference from background sounds generated by electronic devices, which are not effectively addressed by traditional noise cancellation techniques.
Innovation Solution
The implementation of multi-modal audio processing in voice-controlled devices, which involves receiving audio signals through both microphones and electromagnetic signals, allowing for the reduction of noise interference by correlating and subtracting noise signals from the primary audio signal.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional noise cancellation techniques are used, then the device complexity is reduced, but the speech recognition accuracy deteriorates in noisy environments
Solution Approach 1:
The patent introduces electromagnetic signal reception as a new dimension alongside traditional acoustic microphone reception. By receiving the same audio content through two different physical dimensions (acoustic waves and electromagnetic waves), the system creates redundant information channels that enable more effective noise cancellation and improve speech recognition accuracy in noisy environments.
Solution Approach 2:
The patent uses electromagnetic signals as an intermediary to obtain a reference version of the audio content being played by electronic devices. This intermediary signal serves as a template for identifying and subtracting noise components from the acoustic microphone signal, effectively separating desired speech from background electronic device noise.
2Measurement precision
If multi-modal audio processing is implemented, then the speech recognition accuracy improves, but the device complexity increases
Solution Approach 1:
The patent segments the noise cancellation process into distinct modular steps: (1) receiving acoustic signal through microphone, (2) receiving electromagnetic signal, (3) correlating the two signals to identify noise components, (4) subtracting identified noise from acoustic signal. This segmentation makes the complex multi-modal processing more manageable and implementable.
Solution Approach 2:
The patent performs preliminary correlation analysis between acoustic and electromagnetic signals to identify noise components before final speech recognition processing. By pre-identifying and removing noise components in advance, the system simplifies the subsequent speech recognition stage and improves overall accuracy.
3Measurement precision
If noise signals are subtracted from primary audio signal, then the purity of speech signal improves, but the processing time increases
Solution Approach 1:
The patent applies partial action by selectively subtracting only the noise components that are correlated between electromagnetic and acoustic signals, rather than processing the entire signal spectrum. This selective approach removes sufficient noise to improve speech purity while avoiding excessive processing of all signal components, thus reducing processing time.
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 significantly improves the accuracy of speech recognition in voice-controlled devices by effectively filtering out noise from electronic devices, enhancing the responsiveness and reliability of voice-controlled systems in diverse environments.
Implementation Method 1
A microphone converts the sound waves into an audio signal
Implementation Method 2
A typical home may have dozens of such devices, many with stereo or other multi-channel output, such as televisions, radios, smart speakers, telephones, computers, and portable 'boom-boxes' just to name a few. Each of these devices may obtain audio signals and use the audio signal to generate sound waves
Data Source
AI summary
A method for processing an audio signal involves receiving sound waves at a microphone, converting them into a first audio signal, and extracting a second audio signal from an electromagnetic signal received at a receiver. The first audio signal is correlated with the second audio signal to calculate a correlation value. If the correlation value exceeds a threshold, the first audio signal is processed using the second audio signal to reduce unwanted sound contributions, resulting in a processed audio signal. Further processing is then performed on the processed audio signal to determine a characteristic of the desired sound.