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公开(公告)号：US12087320B1
公开(公告)日：2024-09-10
申请号：US17671194
申请日：2022-02-14
Applicant: Amazon Technologies, Inc.
Inventor： Qin Zhang , Qingming Tang , Ming Sun , Chao Wang , Steve Mark Lorusso , Andrew Thomas Bydlon , James Garnet Droppo , Viktor Rozgic , Sripal Mehta , Yang Liu
CPC classification number: G10L25/51 , G10L15/1815 , G10L15/22 , G10L15/30
Abstract: A system may be configured to detect custom acoustic events, where the system generates an acoustic event profile for the custom acoustic event based on a natural language description provided by a user and using an audio sample of the described acoustic event. For example, the user may describe the custom acoustic event as “dog bark.” The system may ask the user questions to refine the description (e.g., dog breed, dog gender, age, etc.). Using an audio sample of the refined description, the system may then determine that audio captured in the user's environment is a potential sample of the custom acoustic event. Such captured audio may be presented to the user for confirmation, and then may be used to detect future occurrences of the custom acoustic event in the user's environment.
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公开(公告)号：US11302329B1
公开(公告)日：2022-04-12
申请号：US16914589
申请日：2020-06-29
Applicant: Amazon Technologies, Inc.
Inventor： Ming Sun , Spyridon Matsoukas , Venkata Naga Krishna Chaitanya Puvvada , Chao Wang , Chieh-Chi Kao
Abstract: A system may include an acoustic event detection component for detecting acoustic events, which may be non-speech sounds. Upon detection of a command to detect a new sound, a device may prompt a user to cause occurrence of the sound one or more times. The acoustic event detection component may then be reconfigured, using audio data corresponding to the occurrences, to detect future occurrences of the event.
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公开(公告)号：US12068001B2
公开(公告)日：2024-08-20
申请号：US18243800
申请日：2023-09-08
Applicant: Amazon Technologies, Inc.
Inventor： Harshavardhan Sundar , Sheetal Laad , Jialiang Bao , Ming Sun , Chao Wang , Chungnam Chan , Cengiz Erbas , Mathias Jourdain , Nipul Bharani , Aaron David Wirshba
CPC classification number: G10L25/51 , G10L15/063 , G10L15/22 , G10L25/78 , G10L2015/0635
Abstract: Techniques for detecting certain acoustic events from audio data are described. A system may perform event aggregation for certain types of events before sending an output to a device representing the event is detected. The system may bypass the event aggregation process for certain types of events that the system may detect with a high level of confidence. In such cases, the system may send an output to the device when the event is detected. The system may be used to detect acoustic events representing presence of a person or other harmful circumstances (such as, fire, smoke, etc.) in a home, an office, a store, or other types of indoor settings.
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公开(公告)号：US11783850B1
公开(公告)日：2023-10-10
申请号：US17216840
申请日：2021-03-30
Applicant: Amazon Technologies, Inc.
Inventor： Harshavardhan Sundar , Sheetal Laad , Jialiang Bao , Ming Sun , Chao Wang , Chungnam Chan , Cengiz Erbas , Mathias Jourdain , Nipul Bharani , Aaron David Wirshba
CPC classification number: G10L25/51 , G10L15/063 , G10L15/22 , G10L25/78 , G10L2015/0635
Abstract: Techniques for detecting certain acoustic events from audio data are described. A system may perform event aggregation for certain types of events before sending an output to a device representing the event is detected. The system may bypass the event aggregation process for certain types of events that the system may detect with a high level of confidence. In such cases, the system may send an output to the device when the event is detected. The system may be used to detect acoustic events representing presence of a person or other harmful circumstances (such as, fire, smoke, etc.) in a home, an office, a store, or other types of indoor settings.
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公开(公告)号：US11043218B1
公开(公告)日：2021-06-22
申请号：US16452964
申请日：2019-06-26
Applicant: Amazon Technologies, Inc.
Inventor： Ming Sun , Thibaud Senechal , Yixin Gao , Anish N. Shah , Spyridon Matsoukas , Chao Wang , Shiv Naga Prasad Vitaladevuni
Abstract: A system processes audio data to detect when it includes a representation of a wakeword or of an acoustic event. The system may receive or determine acoustic features for the audio data, such as log-filterbank energy (LFBE). The acoustic features may be used by a first, wakeword-detection model to detect the wakeword; the output of this model may be further processed using a softmax function, to smooth it, and to detect spikes. The same acoustic features may be also be used by a second, acoustic-event-detection model to detect the acoustic event; the output of this model may be further processed using a sigmoid function and a classifier. Another model may be used to extract additional features from the LFBE data; these additional features may be used by the other models.
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Patent Agency Ranking
公开(公告)号：US10803885B1
公开(公告)日：2020-10-13
申请号：US16023923
申请日：2018-06-29
Applicant: Amazon Technologies, Inc.
Inventor： Chieh-Chi Kao , Chao Wang , Weiran Wang , Ming Sun
Abstract: An audio event detection system that processes audio data into audio feature data and processes the audio feature data using pre-configured candidate interval lengths to identify top candidate regions of the feature data that may include an audio event. The feature data from the top candidate regions are then scored by a classifier, where the score indicates a likelihood that the candidate region corresponds to a desired audio event. The scores are compared to a threshold, and if the threshold is satisfied, the top scoring candidate region is determined to include an audio event.
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公开(公告)号：US10304440B1
公开(公告)日：2019-05-28
申请号：US15198578
申请日：2016-06-30
Applicant: Amazon Technologies, Inc.
Inventor： Sankaran Panchapagesan , Bjorn Hoffmeister , Arindam Mandal , Aparna Khare , Shiv Naga Prasad Vitaladevuni , Spyridon Matsoukas , Ming Sun
Abstract: An approach to keyword spotting makes use of acoustic parameters that are trained on a keyword spotting task as well as on a second speech recognition task, for example, a large vocabulary continuous speech recognition task. The parameters may be optimized according to a weighted measure that weighs the keyword spotting task more highly than the other task, and that weighs utterances of a keyword more highly than utterances of other speech. In some applications, a keyword spotter configured with the acoustic parameters is used for trigger or wake word detection.
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公开(公告)号：US20240071408A1
公开(公告)日：2024-02-29
申请号：US18243804
申请日：2023-09-08
Applicant: Amazon Technologies, Inc.
Inventor： Qingming Tang , Chieh-Chi Kao , Qin Zhang , Ming Sun , Chao Wang , Sumit Garg , Rong Chen , James Garnet Droppo , Chia-Jung Chang
Abstract: A system may include a first acoustic event detection (AED) component configured to detect a predetermined set of acoustic events, and include a second AED component configured to detect custom acoustic events that a user configures a device to detect. The first and second AED components are configured to perform task-specific processing, and may receive as input the same acoustic feature data corresponding to audio data that potentially represents occurrence of one or more events. Based on processing by the first and second AED components, a device may output data indicating that one or more acoustic events occurred, where the acoustic events may be a predetermined acoustic event and/or a custom acoustic event.
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公开(公告)号：US20240071407A1
公开(公告)日：2024-02-29
申请号：US18243800
申请日：2023-09-08
Applicant: Amazon Technologies, Inc.
Inventor： Harshavardhan Sundar , Sheetal Laad , Jialiang Bao , Ming Sun , Chao Wang , Chungnam Chan , Cengiz Erbas , Mathias Jourdain , Nipul Bharani , Aaron David Wirshba
CPC classification number: G10L25/51 , G10L15/063 , G10L15/22 , G10L25/78 , G10L2015/0635
Abstract: Techniques for detecting certain acoustic events from audio data are described. A system may perform event aggregation for certain types of events before sending an output to a device representing the event is detected. The system may bypass the event aggregation process for certain types of events that the system may detect with a high level of confidence. In such cases, the system may send an output to the device when the event is detected. The system may be used to detect acoustic events representing presence of a person or other harmful circumstances (such as, fire, smoke, etc.) in a home, an office, a store, or other types of indoor settings.
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公开(公告)号：US11854538B1
公开(公告)日：2023-12-26
申请号：US16277328
申请日：2019-02-15
Applicant: Amazon Technologies, Inc.
Inventor： Viktor Rozgic , Chao Wang , Ming Sun , Srinivas Parthasarathy
CPC classification number: G10L15/1815 , G10L15/02 , G10L15/063 , G10L15/07 , G10L15/16
Abstract: Described herein is a system for sentiment detection in audio data. The system processes audio frame level features of input audio data using a machine learning algorithm to classify the input audio data into a particular sentiment category. The machine learning algorithm may be a neural network trained using an encoder-decoder method. The training of the machine learning algorithm may include normalization techniques to avoid potential bias in the training data that may occur when the training data is annotated for a perceived sentiment of the speaker.
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