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公开(公告)号：US09813810B1
公开(公告)日：2017-11-07
申请号：US14988047
申请日：2016-01-05
Applicant: Google Inc.
Inventor： Rajeev Conrad Nongpiur
CPC classification number: H04R3/005 , G06N3/08 , G10L25/51 , H04R1/406 , H04R2201/405 , H04R2430/20
Abstract: A neural network is provided for recognition and enhancement of multi-channel sound signals received by multiple microphones, which need not be aligned in a linear array in a given environment. Directions and distances of sound sources may also be detected by the neural network without the need for a beamformer connected to the microphones. The neural network may be trained by knowledge gained from free-field array impulse responses obtained in an anechoic chamber, array impulse responses that model simulated environments of different reverberation times, and array impulse responses obtained in actual environments.
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公开(公告)号：US20180018990A1
公开(公告)日：2018-01-18
申请号：US15211417
申请日：2016-07-15
Applicant: Google Inc.
Inventor： CHANWOO KIM , Rajeev Conrad Nongpiur , TARA SAINATH
CPC classification number: G10L19/008 , G10L19/0017 , G10L25/30 , G10L25/72
Abstract: A sensor device may include a computing device in communication with multiple microphones. A neural network executing on the computing device may receive audio signals from each microphone. One microphone signal may serve as a reference signal. The neural network may extract differences in signal characteristics of the other microphone signals as compared to the reference signal. The neural network may combine these signal differences into a lossy compressed signal. The sensor device may transmit the lossy compressed signal and the lossless reference signal to a remote neural network executing in a cloud computing environment for decompression and sound recognition analysis.
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公开(公告)号：US20170353789A1
公开(公告)日：2017-12-07
申请号：US15170348
申请日：2016-06-01
Applicant: Google Inc.
Inventor： Chanwoo Kim , Rajeev Conrad Nongpiur , Arun Narayanan
CPC classification number: H04R3/005 , G10L25/30 , H04R5/027 , H04R2201/401 , H04R2430/20 , H04S2400/11 , H04S2400/15 , H04S2420/01
Abstract: A system for estimating the location of a stationary or moving sound source includes multiple microphones, which need not be physically aligned in a linear array or a regular geometric pattern in a given environment, an auralizer that generates auralized multi-channel signals based at least on array-related transfer functions and room impulse responses of the microphones as well as signal labels corresponding to the auralized multi-channel signals, a feature extractor that extracts features from the auralized multi-channel signals for efficient processing, and a neural network that can be trained to estimate the location of the sound source based at least on the features extracted from the auralized multi-channel signals and the corresponding signal labels.
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公开(公告)号：US20160379456A1
公开(公告)日：2016-12-29
申请号：US14748589
申请日：2015-06-24
Applicant: Google Inc.
Inventor： Rajeev Conrad Nongpiur , Michael Dixon
IPC: G08B13/16
CPC classification number: G08B13/1672 , G08B13/08 , G08B25/008 , G08B29/188
Abstract: Systems and methods of a security system are provided, including detecting, by a sensor, a sound event, and selecting, by a processor coupled to the sensor, at least a portion of sound data captured by the sensor that corresponds to at least one sound feature of the detected sound event. The systems and methods include classifying the at least one sound feature into one or more sound categories, and determining, by a processor, based upon a database of home-specific sound data, whether the at least one sound feature is a human-generated sound. A notification can be transmitted to a computing device according to the sound event.
Abstract translation: 提供了一种安全系统的系统和方法，包括由传感器检测声音事件，并且由耦合到传感器的处理器选择由传感器捕获的对应于至少一个声音的声音数据的至少一部分 检测到的声音事件的特征。 所述系统和方法包括将至少一个声音特征分类为一个或多个声音类别，以及由处理器基于家庭特定声音数据的数据库确定所述至少一个声音特征是否是人造声音 。 可以根据声音事件将通知发送到计算设备。
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公开(公告)号：US20160335488A1
公开(公告)日：2016-11-17
申请号：US14713619
申请日：2015-05-15
Applicant: Google Inc.
Inventor： Rajeev Conrad Nongpiur , Michael Dixon
CPC classification number: G10L25/51 , G08B13/1672 , G10L25/18
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.
Abstract translation: 一种使用现有分布式系统的传感器和处理器的系统和方法，可单独或与其他系统，网络或基于云的服务合作运行，以增强环境（如家庭）中声音事件的检测和分类， ，同时具有较低的计算复杂度。 该系统和方法提供了功能，其中有助于区分声音的最相关特征从音频信号中提取，然后根据提取的特征是否对应于应该导致与用户通信的声音事件来分类。 门限值和其他变量可以通过在定义的环境中对已知声音的音频信号进行训练来确定，并且被实现为将人和宠物声音与其他声音区分开来，并且补偿音频信号的幅度，不同大小和混响特性的变化 环境和麦克风响应的变化。
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Patent Agency Ranking
公开(公告)号：US10339929B2
公开(公告)日：2019-07-02
申请号：US15634863
申请日：2017-06-27
Applicant: Google Inc.
Inventor： Chan Woo Kim , Rajeev Conrad Nongpiur , Vijayaditya Peddinti , Michiel Bacchiani
Abstract: An example method includes receiving, by a computing system, an indication of one or more audible sounds that are detected by a first sensing device, the one or more audible sounds originating from a user; determining, by the computing system and based at least in part on an indication of one or more signals detected by a second sensing device, a distance between the user and the second sensing device; determining, by the computing system and based at least in part on the indication of the one or more audible sounds, one or more acoustic features that are associated with the one or more audible sounds; and determining, by the computing system, and based at least in part on the one or more acoustic features and the distance between the user and the second sensing device, one or more words that correspond to the audible sounds.
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公开(公告)号：US10068445B2
公开(公告)日：2018-09-04
申请号：US14748589
申请日：2015-06-24
Applicant: Google Inc.
Inventor： Rajeev Conrad Nongpiur , Michael Dixon
Abstract: Systems and methods of a security system are provided, including detecting, by a sensor, a sound event, and selecting, by a processor coupled to the sensor, at least a portion of sound data captured by the sensor that corresponds to at least one sound feature of the detected sound event. The systems and methods include classifying the at least one sound feature into one or more sound categories, and determining, by a processor, based upon a database of home-specific sound data, whether the at least one sound feature is a human-generated sound. A notification can be transmitted to a computing device according to the sound event.
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公开(公告)号：US09992570B2
公开(公告)日：2018-06-05
申请号：US15170924
申请日：2016-06-01
Applicant: Google Inc.
Inventor： Chanwoo Kim , Rajeev Conrad Nongpiur , Ananya Misra
CPC classification number: H04R3/005 , H04R5/027 , H04R29/005 , H04R29/006 , H04R2201/401 , H04R2430/20
Abstract: A method for auralizing a multi-microphone device. Path information for one or more sound paths using dimensions and room reflection coefficients of a simulated room for one of a plurality of microphones included in a multi-microphone device is determined. An array-related transfer functions (ARTFs) for the one of the plurality of microphones is retrieved. The auralized impulse response for the one of the plurality of microphones is generated based at least on the retrieved ARTFs and the determined path information.
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公开(公告)号：US09965685B2
公开(公告)日：2018-05-08
申请号：US14737678
申请日：2015-06-12
Applicant: Google Inc.
Inventor： Yoky Matsuoka , Rajeev Conrad Nongpiur , Michael Dixon
IPC: G10L25/51 , G10L25/03 , G10L25/72 , G10L25/78 , G06K9/00 , H04R3/00 , G08B21/02 , G10L25/27 , G08B1/08
CPC classification number: G06K9/00771 , G06K9/00979 , G06K9/46 , G06K9/6267 , G08B1/08 , G08B21/0208 , G10L25/27 , G10L25/51 , G10L25/72 , G10L25/78 , H04R3/00 , H04R2410/05
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.
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公开(公告)号：US20180020286A1
公开(公告)日：2018-01-18
申请号：US15207707
申请日：2016-07-12
Applicant: Google Inc.
Inventor： Rajeev Conrad Nongpiur
CPC classification number: H04R3/005 , H04R1/02 , H04R1/04 , H04R1/222 , H04R1/326 , H04R1/342 , H04R1/38 , H04R1/406 , H04R5/027 , H04R2201/401 , H04R2201/403 , H04R2430/20 , H04R2499/11
Abstract: Methods and apparatus relating to microphone devices and signal processing techniques are provided. In an example, a microphone device can detect sound, as well as enhance an ability to perceive at least a general direction from which the sound arrives at the microphone device. In an example, a case of the microphone device has an external surface which at least partially defines funnel-shaped surfaces. Each funnel-shaped surface is configured to direct the sound to a respective microphone diaphragm to produce an auralized multi-microphone output. The funnel-shaped surfaces are configured to cause direction-dependent variations in spectral notches and frequency response of the sound as received by the microphone diaphragms. A neural network can device-shape the auralized multi-microphone output to create a binaural output. The binaural output can be auralized with respect to a human listener.
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