Abstract
Extended reality (XR) devices rely on multiple microphones with consistent sensitivity to provide optimal audio performance. When microphone sensitivity degrades over time, in a standard calibration approach for microphones, ambient noise is used to adjust the spectral differences between microphones. However, if the noise is directional or not perfectly diffused, the calibration may have inaccuracies. This disclosure describes automatic recalibration of microphone sensitivity for XR devices by leveraging the directional nature of device loudspeakers. The techniques described herein can be utilized to detect problems with an arbitrary number of microphones. By utilizing excitation signals from the device loudspeakers and leveraging their directional properties, the described techniques minimize external interference and enable precise microphone recalibration while also helping identify potential microphone malfunctions. The techniques described herein can also be used to identify potential microphone malfunctions.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Nongpiur, Rajeev, "Microphone Self-calibration for Extended Reality (XR) Devices", Technical Disclosure Commons, (November 17, 2024)
https://www.tdcommons.org/dpubs_series/7545