Personalized Spatial Audio Repositioning for Calls and Music
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Solution Overview
Problem
Existing audio systems fail to seamlessly continue music playback during phone calls, as they often mute music or poorly distinguish between audio sources due to non-individualized spatial audio positioning, leading to a suboptimal user experience, especially with headphones.
Innovation Solution
The use of personalized spatial audio transfer functions, such as individualized Binaural Room Impulse Responses (BRIRs) and Head Related Transfer Functions (HRTFs), to position audio streams distinctly as foreground and background sources, enhancing the listener's ability to differentiate between them by simulating head and torso interactions with audio signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If music is muted during phone calls to prioritize call audio, then call audio quality is improved, but music playback continuity deteriorates
Solution Approach 1:
The audio output is segmented into distinct spatial channels: foreground audio (phone call) and background audio (music). By spatially separating these audio streams rather than mixing them in a single channel, the system allows both to coexist without mutual interference, enabling call audio to be clearly heard while music continues playing uninterrupted in the background.
Solution Approach 2:
The patent transitions from traditional mono/stereo audio mixing to three-dimensional spatial audio positioning. By adding the spatial dimension (foreground/background depth positioning), the system creates separate auditory layers that allow simultaneous playback of call and music without the need to mute either, resolving the contradiction between call quality and music continuity.
2Device complexity
If multiple audio sources are mixed in a single channel, then device complexity is reduced, but audio source distinguishability deteriorates
Solution Approach 1:
The audio processing system segments multiple audio sources into distinct spatial categories (foreground and background positions). Instead of complex multi-channel mixing, the system uses simple spatial positioning tags assigned to each audio source, allowing the brain to naturally separate and identify different sources based on their spatial location, thus maintaining simplicity while improving distinguishability.
Solution Approach 2:
Different spatial qualities are assigned to different audio sources based on their importance and type. Foreground audio (calls, notifications) is positioned in the foreground with higher prominence, while background audio (music, ambient sounds) is positioned in the background. This local differentiation of spatial quality allows easy distinguishability without requiring complex processing of all audio sources equally.
Data Source
AI summary
An audio rendering system includes a processor that combines audio input signals with personalized spatial audio transfer functions preferably including room responses. The personalized spatial audio transfer functions are selected from a database having a plurality of candidate transfer function datasets derived from in-ear microphone measurements for a plurality of individuals. Alternatively, the personalized transfer function datasets are derived from actual in-ear measurements of the listener. Foreground and background positions are designated and matched with transfer function pairs from the selected dataset for the foreground and background direction and distance. Two channels of input audio such as voice and music are processed. When a voice communication such as a phone call is accepted the music being rendered is moved from a foreground to a background channel corresponding to a background spatial audio position using the personalized transfer functions. The voice call is simultaneously transferred to the foreground channel.