Sound event detection

• US 10,074,383 B2
• Filed: 10/30/2017
• Issued: 09/11/2018
• Est. Priority Date: 05/15/2015
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google LLC (Alphabet Inc.)
• Inventors: Nongpiur, Rajeev Conrad, Dixon, Michael
• Primary Examiner(s): Zhang, Leshui
• Application Number:
  US15/797,991
• Publication Number:
  US 20180047415A1
• Time in Patent Office: 316 Days
• Field of Search: 381 56, 381302, 381 86, 381 12, 381 14, 381 16, 381 26, 381 28, 381 57, 381 61, 381321, 381333, 381334, 381 91, 381 92, 381 93, 381 941- 948, 381 95, 381 97, 381 98, 381100, 381101, 381102, 381103, 381118, 381119, 381120, 381122, 381 731, 381 74, 704E17002, 704231, 704246, 704251, 704E17011, 704E15001, 704E15002, 704E15003, 704E15004, 704E15038, 704E15039, 704E1504, 704E15044, 704E15047, 700 94
• CPC Class Codes: G08B 13/1672 using sonic detecting means, e.g. a microphone operating in the audio frequency range
• CPC Class Codes: G10L 25/18 the extracted parameters being spectral information of each sub-band
• CPC Class Codes: G10L 25/51 for comparison or discrimination

Abstract

A system and method for the use of sensors and processors of existing, distributed systems, operating individually or in cooperation with other systems, networks or cloud-based services to enhance the detection and classification of sound events in an environment (e.g., a home), while having low computational complexity. The system and method provides functions where the most relevant features that help in discriminating sounds are extracted from an audio signal and then classified depending on whether the extracted features correspond to a sound event that should result in a communication to a user. Threshold values and other variables can be determined by training on audio signals of known sounds in defined environments, and implemented to distinguish human and pet sounds from other sounds, and compensate for variations in the magnitude of the audio signal, different sizes and reverberation characteristics of the environment, and variations in microphone responses.

Claims

1. An environmental data monitoring and reporting system, comprising:

a device sensor that detects sound in an area and generates an audio signal based on the detected sound;

a device processor communicatively coupled to the device sensor, wherein the device processor is configured to convert the audio signal received from the device sensor into low-resolution audio signal data comprising a plurality of low-resolution feature vectors representative of the detected sound, and to analyze the low-resolution audio signal data, at the device processor level, to identify the detected sound as one of either a sound belonging to a first sound category, or a sound belonging to a second sound category to generate an identity of the detected sound, and provide a communication regarding the identity of the detected sound; and

a device communication interface communicatively coupled to the device processor, wherein the device communication interface is configured to send the communication,

wherein the device processor is configured to;

implement a frequency domain conversion of the audio signal;

implement a plurality of bandwidth filters, a plurality of median filters, a plurality of range filters, and a plurality of summers, to extract low-resolution feature vectors that distinguish the detected sounds;

implement a state classifier to determine state transition conditions by comparing the low-resolution feature vectors to threshold values that distinguish the first and second sound categories and to generate outputs indicating occurrences of the distinguished first and second sound categories; and

implement a detector to detect an occurrence of the first sound category, based on the outputs of the state classifier and generate a corresponding message in response.

2. The environmental data monitoring and reporting system of claim 1, further comprising a Fast Fourier Transform element, implemented by the device processor, to perform the frequency domain conversion of the audio signal, on a frame-by-frame basis.

3. The environmental data monitoring and reporting system of claim 1, wherein:

the plurality of bandwidth filters are configured to divide bands of the frequency domain conversion;

the plurality of median filters are configured to median filter the divided bands;

the plurality of range filters are configured to filter a range of the divided bands after the divided bands are median filtered; and

the plurality of summers are configured to subtract a minimum band range value from a maximum band range value to calculate the plurality of low-resolution feature vectors that distinguish the first and second sound categories, on a frame-by-frame basis.

4. The environmental data monitoring and reporting system of claim 1, wherein:

the state classifier element is configured to determine the state transition conditions by comparing the plurality of low-resolution feature vectors to the threshold values that distinguish the first and second sound categories and to generate outputs indicating occurrences of the distinguished first and second sound categories and generate the outputs indicating the occurrences of the first and second sound categories, on a frame-by-frame basis.

5. The environmental data monitoring and reporting system of claim 4, wherein the device processor is configured to train on low-resolution audio signal data of known sound categories in defined areas to determine the threshold values that distinguish the first and second sound categories and that compensate for low-resolution audio signal data, area and sensor variations.

6. The environmental data monitoring and reporting system of claim 1, wherein:

the detector is configured to detect the occurrence of the first sound category, which corresponds to an area human or pet occupancy; and

the device communication interface is configured to communicate a message in response to the detected occurrence of the first sound category.

7. The environmental data monitoring and reporting system of claim 6, wherein the detector element is configured to statistically analyze the outputs indicating the occurrences of the sound categories to detect a likelihood of an occurrence of a sound category indicating an area human or pet occupancy.

8. An environmental data monitoring and reporting system, comprising:

a device sensor, comprising a microphone, that detects a condition comprising one or more sounds in an area and that generates an audio signal based on the detected condition;

a device processor communicatively coupled to the device sensor, wherein the device processor is configured to receive the audio signal and convert the audio signal received from the device sensor into low-resolution signal data comprising a plurality of low-resolution feature vectors representative of the one or more sounds in the area and to analyze the low-resolution audio signal data, at the device processor level, by;

implementing a frequency domain conversion element, a plurality of bandwidth filters, a plurality of median filters, a plurality of range filters, and a plurality of summers, to perform a frequency domain conversion of the audio signal data and extract low-resolution feature vectors that distinguish the detected condition,

implementing a state classifier to compare the low-resolution feature vectors to threshold values that distinguish the detected condition to generate distinguished categories,

generating outputs indicating occurrences of the distinguished categories, and

implementing a detector element to detect the detected condition, which represents one of either a sound belonging to a first sound category, or a sound belonging to a second sound category, and generate a corresponding message in response; and

a device communication interface communicatively coupled to the device processor, wherein the device communication interface is configured to send the message.

9. The environmental data monitoring and reporting system of claim 8, wherein:

a Fast Fourier Transform element is configured to perform the frequency domain conversion of the signal data;

the plurality of bandwidth filters is configured to divide bands of the frequency domain conversion;

the plurality of median filters is configured to median filter the divided bands;

the plurality of range filters is configured to filter a range of the divided bands after the divided bands are median filtered; and

the plurality of summers is configured to subtract a minimum band range value from a maximum band range value to calculate the plurality of low-resolution feature vectors that distinguish detected conditions.

10. The environmental data monitoring and reporting system of claim 8, wherein:

the state classifier is configured to compare the plurality of low-resolution feature vectors to the threshold values and generate the outputs indicating the occurrences of the first or second sound categories.

11. The environmental data monitoring and reporting system of claim 10, wherein the device processor is configured to train on low-resolution signal data of known condition categories in defined areas to determine the threshold values that distinguish the condition categories and that compensate for signal data, area and sensor variations.

12. The environmental data monitoring and reporting system of claim 8, wherein:

the detector element is configured to detect the occurrence of a sound category indicating an area human or pet occupancy; and

the device communication interface is configured to communicate the message in response to the detected occurrence of the sound category indicating an area human or pet occupancy.

13. A method for controlling an environmental data monitoring and reporting system, comprising:

detecting sound in an area and generating an audio signal based on the detected sound; and

converting the audio signal into low-resolution audio signal data comprising a plurality of low-resolution feature vectors representative of the sound in the area, and analyzing the low-resolution audio signal data, at a device processor level, to identify the detected sound as one of either a sound belonging to a first sound category, or a sound belonging to a second sound category to generate an identity of the sound, and provide a communication regarding the identity of the sound,

wherein the converting comprises performing a frequency domain conversion of the audio signal and extracting low-resolution feature vectors that distinguish the first and second sound categories, where the extracting is performed using a plurality of bandwidth filters, a plurality of median filters, a plurality of range filters, and a plurality of summers, to extract the low-resolution feature vectors, and

the analyzing comprises determining state transition conditions by comparing the low-resolution feature vectors to threshold values that distinguish the first and second sound categories and generating outputs indicating occurrences of the distinguished sound categories.

14. The method of claim 13, wherein the analyzing step further comprises detecting the occurrence of one of the first or second sound categories that indicates an area human or pet occupancy.

15. The method of claim 13, further comprising training on low-resolution audio signal data of known sound categories in defined areas to determine the threshold values that distinguish the sound categories and that compensate for audio signal, area and sensor variations.