Patent Document ID: 10068587
Application ID: 14745461
Patent Status: 1

Claim One:
1. A method for detecting the presence of one or more individual human occupants in an indoor environment comprising: providing a database of a plurality of models for determining presence of one or more individual human occupants based upon acoustic features, with each model of the plurality of models associated with a respective individual of a plurality of individuals; detecting acoustic events in an audio signal obtained from the indoor environment; determining human presence of a first individual human in the indoor environment by: comparing the acoustic events with each of the plurality of models; computing a likelihood score for each of the plurality of models based at least on the comparing the acoustic events with each of the plurality of models; identifying a first model of the plurality of models having a greatest likelihood score, the first model associated with the first individual human; and determining that the first individual human is present in the indoor environment based at least in part on the first model associated with the first individual human being identified as having a greatest likelihood score; and refining at least one of the models of the plurality of models based at least in part on the determining that the first individual human is present in the indoor environment, so that the models over time become more accurate and more specific to characteristics of the acoustic features of each of the respective individual human occupants and the particular indoor environment, wherein refining the models includes: starting with generic models to detect, from acoustic features, the presence and absence of each of the individual human occupants in the indoor environment; and during high-detection probability of presence of a particular individual human occupant, modifying a human-presence model for that particular individual human occupant so that relevant acoustic features specific to the particular individual human occupant and the indoor environment are emphasized, thereby improving the accuracy of the human-presence model for that particular individual human occupant over time.