Bose Corporation

Chuan-Che Huang

Jeremy Kemmerer

Todd Richard Reily

Yang Liu

Christopher Alexis Kotelly

Shuo Zhang

Junyan Jiang

Lauren Westendorf

Trevor Caldwell

Daniel M Gauger, Jr

Elio Dante Querze

Mark Raymond Blewett

Elio Querze, Iii

Xiao Quan

Berker Banar

Various implementations include adaptive masking of environmental sound. Particular implementations are configured to adjust a masking sound based on one or more detected environmental sound sources. An example method includes: measuring environmental sound proximate to an audio device, outputting a masking sound at the audio device, and adjusting at least one of: a volume of the masking sound, a spectrum of the masking sound, or content of the masking sound based on the measured environmental sound.

Environmentally adaptive masking sound

Aspects of the present disclosure provide techniques, including devices and system implementing the techniques, to provide feedback to a user of an event when the user is wearing a wearable device. For example, the wearable device may provide high quality noise canceling audio playback to the user, lowering the user's situation awareness. The techniques include measuring ambient sound using two or more microphones on the wearable device. The measured ambient sound is used to determine a related event worth relaying to the user. Based on the location attribute and sound properties, the nature and/or classification of the event may be ascertained using pattern recognition algorithms according to user threshold settings. Insignificant events that the user prefers to ignore will be ruled out by the algorithm. Upon determining the event that merits the user's attention, the wearable device provides feedback to the user indicating the nature and location of the event.

Hearing augmentation and wearable system with localized feedback

Aspects of the present disclosure provide techniques, including devices and system implementing the techniques, to provide feedback to a user of an event when the user is wearing a wearable device. For example, the wearable device may provide high quality noise canceling audio playback to the user, lowering the user's situation awareness. The techniques include measuring ambient sound using two or more microphones on the wearable device. The event is determined based on the measured ambient sound. A location attribute of the event is determined. A deep learning algorithm may be used to identify the nature and/or classification of the event and rule out events that the user prefers to ignore. Upon determining the event that merits the user's attention, the user is provided feedback of the determined event and the location attribute, the feedback indicating the nature and location of the event.

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Framingham, MA, United States of America

Chuan-Che Huang