Method and system for detecting an audio event for smart home devices
First Claim
1. A method for detecting a signature event associated with an audio feature, comprising:
- on an electronic device having one or more processors and memory storing one or more programs for execution by the one or more processors, automatically and without user intervention;
obtaining from a remote server a classifier model that distinguishes an audio feature from a plurality of alternative features and ambient noises, wherein the classifier model is determined by the remote server according to a number of false positives generated by the classifier model, predefined capabilities of the electronic device and ambient sound characteristics of the electronic device, the predefined capabilities of the electronic device comprising one or more of computational capabilities, storage capabilities, and caching capabilities;
obtaining audio data associated with an audio signal;
splitting the audio data to a plurality of sound components each associated with a respective frequency or frequency band and including a series of time windows;
statistically analyzing each of the plurality of sound components across the series of time windows;
extracting a feature vector from the plurality of sound components based on the statistical analysis, the feature vector including a plurality of elements that are arranged according a predetermined order;
classifying the extracted feature vector based on the classifier model to obtain a probability value indicating whether the audio signal includes the audio feature within the series of time windows; and
detecting the signature event associated with the audio feature based on the probability value and issuing an alert indicating occurrence of the signature event.
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Accused Products
Abstract
This application discloses a method implemented by an electronic device to detect a signature event (e.g., a baby cry event) associated with an audio feature (e.g., baby sound). The electronic device obtains a classifier model from a remote server. The classifier model is determined according to predetermined capabilities of the electronic device and ambient sound characteristics of the electronic device, and distinguishes the audio feature from a plurality of alternative features and ambient noises. When the electronic device obtains audio data, it splits the audio data to a plurality of sound components each associated with a respective frequency or frequency band and including a series of time windows. The electronic device further extracts a feature vector from the sound components, classifies the extracted feature vector to obtain a probability value according to the classifier model, and detects the signature event based on the probability value.
52 Citations
23 Claims
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1. A method for detecting a signature event associated with an audio feature, comprising:
on an electronic device having one or more processors and memory storing one or more programs for execution by the one or more processors, automatically and without user intervention; obtaining from a remote server a classifier model that distinguishes an audio feature from a plurality of alternative features and ambient noises, wherein the classifier model is determined by the remote server according to a number of false positives generated by the classifier model, predefined capabilities of the electronic device and ambient sound characteristics of the electronic device, the predefined capabilities of the electronic device comprising one or more of computational capabilities, storage capabilities, and caching capabilities; obtaining audio data associated with an audio signal; splitting the audio data to a plurality of sound components each associated with a respective frequency or frequency band and including a series of time windows; statistically analyzing each of the plurality of sound components across the series of time windows; extracting a feature vector from the plurality of sound components based on the statistical analysis, the feature vector including a plurality of elements that are arranged according a predetermined order; classifying the extracted feature vector based on the classifier model to obtain a probability value indicating whether the audio signal includes the audio feature within the series of time windows; and detecting the signature event associated with the audio feature based on the probability value and issuing an alert indicating occurrence of the signature event. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21)
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22. A method for detecting a signature event associated with an audio feature, comprising:
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on an electronic device having one or more processors and memory storing one or more programs for execution by the one or more processors, automatically and without user intervention; obtaining audio data associated with an audio signal; splitting the audio data to a plurality of sound components each associated with a respective frequency or frequency band and including a series of time windows; statistically analyzing each of the plurality of sound components across the series of time windows; extracting a feature vector from the plurality of sound components based on the statistical analysis, the feature vector including a first subset of elements associated with energy levels of a first subset of sound components, and a second subset of elements associated with harmonic characteristics of a second subset of sound components, wherein the first and second subsets of elements in the feature vector are arranged according a predetermined order; classifying the extracted feature vector based on a classifier model provided by a remote server to obtain a probability value indicating whether the audio signal includes the audio feature within the series of time windows, wherein the classifier is configured to recognize the audio feature according to feature vectors that include elements arranged according to the predetermined order, wherein the classifier model is determined by the remote server based on a number of false positives generated by the classifier model and the predefined capabilities of the electronic device comprising one or more of computational capabilities, storage capabilities, and caching capabilities; detecting the signature event associated with the audio feature based on the probability value and issuing an alert indicating occurrence of the signature event.
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23. An electronic device for detecting a signature event associated with an audio feature, the electronic device comprising:
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one or more processors; and memory storing one or more programs to be executed by the one or more processors, the one or more programs comprising instructions for; obtaining acoustic data associated with an audio signal; splitting the audio data to a plurality of sound components each associated with a respective frequency or frequency band and including a series of time windows; statistically analyzing each of the plurality of sound components across the series of consecutive time windows; extracting a feature vector from the plurality of sound components based on the statistical analysis, the feature vector including a first subset of elements associated with energy levels of a first subset of sound components, and a second subset of elements associated with harmonic characteristics of a second subset of sound components, wherein the first and second subsets of elements in the feature vector are arranged according a predetermined order; classifying the extracted feature vector based on a classifier model provided by a remote server to obtain a probability value indicating whether the audio signal includes the audio feature within the series of consecutive time windows, wherein the classifier is configured to recognize the audio feature according to feature vectors that include elements arranged according to the predetermined order, wherein the classifier model is determined by the remote server based on a number of false positives generated by the classifier model and the predefined capabilities of the electronic device comprising one or more of computational capabilities, storage capabilities, and caching capabilities; detecting the signature event associated with the audio feature based on the probability value and issuing an alert indicating occurrence of the signature event.
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Specification