Amazon Technologies, Inc.

Md Tamzeed Islam

Trausti Thor Kristjansson

Wontak Kim

Mrudula V Athi

Mahathir Monjur

Techniques for presence detection based on multi modal sensors are described. In an example, a computer system determines first data indicating a first prediction of presence detection within a space. The first data is generated based on first sensor data. The computer system determines second data indicating a second prediction of presence detection within the space. The second data is generated based on second sensor data. The second sensor data is of a different type than the first sensor data. The computer system generates third data indicating a third prediction of presence detection within the space based on the first data, the second data, and a fusion model. The fusion model is configured to generate the third data by at least using associations between presence detections, latent variables, and observed variables. The observed variables correspond to the first data and the second data. The latent variables include sensor-triggering events.

Presence detection based on multiple sensors

A system configured to perform user orientation estimation to determine a direction a user is facing using a deep neural network (DNN). As a directionality of human speech increases with frequency, the DNN may estimate the user orientation by comparing high-frequency components detected by each of the multiple devices. For example, a group of devices may individually generate feature data, which represents audio features and spatial information, and send the feature data to the other devices. Thus, each device in the group receives feature data generated by the other devices and processes this feature data using a DNN to determine an estimate of user orientation. In some examples, the DNN may also generate sound source localization (SSL) data and/or a confidence score associated with the user orientation estimate. A post-processing step may process the individual user orientation estimates generated by the individual devices and determine a final user orientation estimate.

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Stow, MA, United States of America

Md Tamzeed Islam