Neural Attention Control of Internal and Real-World Audio
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Solution Overview
Problem
Existing audio output devices struggle to dynamically adjust audio output based on a user's auditory attention between internal audio data and real-world audio, leading to suboptimal listening experiences and inefficient use of active noise cancellation.
Innovation Solution
An apparatus and method that utilize neural activity measurements to identify which audio data has the user's attention, controlling the output of audio data via loudspeakers by adjusting noise cancellation, amplification, and sound capture based on this identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If active noise cancellation is continuously applied to block real-world audio, then noise cancellation performance is improved, but the system cannot respond to user's changing auditory attention between internal audio and real-world audio
Solution Approach 1:
The system uses EEG sensors to continuously monitor the user's auditory attention state and provides feedback to dynamically adjust the noise cancellation level. When the user pays attention to real-world audio, the system reduces noise cancellation; when the user focuses on internal audio, the system enhances noise cancellation. This closed-loop feedback mechanism resolves the contradiction by making noise cancellation adaptive rather than static.
Solution Approach 2:
The patent implements dynamic adjustment of noise cancellation levels based on real-time detection of user's auditory attention through neural activity measurement. The system transitions from a static noise cancellation mode to a dynamic mode where the cancellation level continuously adapts to the user's changing attention state, allowing optimal performance across different listening scenarios.
2Reliability
If all audio signals are output at full gain, then audio quality is maintained, but power consumption increases and irrelevant audio signals waste user's attention
Solution Approach 1:
The system applies different gain levels to different audio sources based on the user's auditory attention. Instead of uniformly amplifying all audio signals, the system selectively amplifies only the audio source that the user is currently attending to, while attenuating irrelevant audio sources. This local differentiation of gain levels maintains audio quality for relevant content while reducing power consumption and avoiding user distraction from irrelevant sounds.
3Adaptability or versatility
If the system monitors neural activity continuously to track auditory attention, then adaptability to user needs is improved, but device complexity and computational load increase
Solution Approach 1:
The patent introduces an intermediary processing layer that translates complex EEG neural activity signals into simplified auditory attention states. Rather than directly processing raw neural data for all system decisions, the intermediary component interprets neural patterns and generates high-level attention state information that drives the audio output control. This intermediary approach reduces the computational burden and simplifies the overall system architecture while maintaining high adaptability.
Data Source
AI summary
Example embodiments relate to an apparatus, method and computer-program product relating to controlling output of audio data. An example method is disclosed, comprising outputting a first set of audio data via one or more loudspeakers, capturing, via one or more microphones, a real-world audio scene to provide a second set of audio data for output via the one or more loudspeakers and identifying which of the first set of audio data and at least part of the real-world audio scene has the auditory attention of the user based on a measured neural activity of the user. The method may also comprise controlling output of at least some of the first and/or second set of audio data via the one or more loudspeakers based on the identification.