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公开(公告)号：US20230186902A1
公开(公告)日：2023-06-15
申请号：US17547547
申请日：2021-12-10
Applicant: Amazon Technologies, Inc.
Inventor： Gengshen Fu , Huitian Lei , Sai Kiran Venkata Subramanya Rupanagudi , Yuriy Mishchenko , Cody Jacques
CPC classification number: G10L15/16 , G10L15/22 , G10L2015/088
Abstract: A device is configured to detect multiple different wakewords. A device may operate a joint encoder that operates on audio data to determine encoded audio data. The device may operate multiple different decoders which process the encoded audio data to determine if a wakeword is detected. Each decoder may correspond to a different wakeword. The decoders may use fewer computing resources than the joint encoder, allowing for the device to more easily perform multiple wakeword processing. Enabling/disabling wakeword(s) may involve the reconfiguring of a wakeword detector to add/remove data for respective decoder(s).
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公开(公告)号：US11308939B1
公开(公告)日：2022-04-19
申请号：US16140737
申请日：2018-09-25
Applicant: Amazon Technologies, Inc.
Inventor： Yixin Gao , Ming Sun , Varun Nagaraja , Gengshen Fu , Chao Wang , Shiv Naga Prasad Vitaladevuni
Abstract: A system and method performs wakeword detection and automatic speech recognition using the same acoustic model. A mapping engine maps phones/senones output by the acoustic model to phones/senones corresponding to the wakeword. A hidden Markov model (HMM) may determine that the wakeword is present in audio data; the HMM may have multiple paths for multiple wakewords or may have multiple models. Once the wakeword is detected, ASR is performed using the acoustic model.
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公开(公告)号：US10777189B1
公开(公告)日：2020-09-15
申请号：US15832259
申请日：2017-12-05
Applicant: Amazon Technologies, Inc.
Inventor： Gengshen Fu , Shiv Naga Prasad Vitaladevuni , Paul McIntyre , Shuang Wu
Abstract: Techniques for using a dynamic wakeword detection threshold are described. A device detects a wakeword in audio data using a first wakeword detection threshold value. Thereafter, the device receives audio including speech. If the device receives the audio within a predetermined duration of time after detecting the previous wakeword, the device attempts to detect a wakeword in second audio data, corresponding to the audio including the speech, using a second, lower wakeword detection threshold value.
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公开(公告)号：US12190875B1
公开(公告)日：2025-01-07
申请号：US17490572
申请日：2021-09-30
Applicant: Amazon Technologies, Inc.
Inventor： Eli Joshua Fidler , Aaron Challenner , Zoe Adams , Sree Hari Krishnan Parthasarathi , Gengshen Fu
IPC: G10L15/00 , G10L15/02 , G10L15/22 , G10L15/08 , G10L15/187
Abstract: Systems and methods for preemptive wakeword detection are disclosed. For example, a first part of a wakeword is detected from audio data representing a user utterance. When this occurs, on-device speech processing is initiated prior to when the entire wakeword is detected. When the entire wakeword is detected, results from the on-device speech processing and/or the audio data is sent to a speech processing system to determine a responsive action to be performed by the device. When the entire wakeword is not detected, on-device processing is canceled and the device refrains from sending the audio data to the speech processing system.
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Patent Agency Ranking
公开(公告)号：US20240412728A1
公开(公告)日：2024-12-12
申请号：US18333041
申请日：2023-06-12
Applicant: Amazon Technologies, Inc.
Inventor： Michael Thomas Peterson , Gengshen Fu , Aaron Challenner , Rong Chen , Cody Jacques , Stefan M Bradstreet
Abstract: A device is configured to detect multiple different wakewords. A device may operate a joint encoder that operates on audio data to determine encoded audio data. The device may operate multiple different decoders which process the encoded audio data to determine if a wakeword is detected. Each decoder may correspond to a different wakeword. The decoders may use fewer computing resources than the joint encoder, allowing for the device to more easily perform multiple wakeword processing. Enabling/disabling wakeword(s) may involve the reconfiguring of a wakeword detector to add/remove data for respective decoder(s). Specific decoders may be activated/deactivated depending on device context, thereby efficiently managing device resources.
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公开(公告)号：US20250149036A1
公开(公告)日：2025-05-08
申请号：US18966827
申请日：2024-12-03
Applicant: Amazon Technologies, Inc.
Inventor： Eli Joshua Fidler , Aaron Challenner , Zoe Adams , Sree Hari Krishnan Parthasarathi , Gengshen Fu
IPC: G10L15/22 , G10L15/02 , G10L15/08 , G10L15/187
Abstract: Systems and methods for preemptive wakeword detection are disclosed. For example, a first part of a wakeword is detected from audio data representing a user utterance. When this occurs, on-device speech processing is initiated prior to when the entire wakeword is detected. When the entire wakeword is detected, results from the on-device speech processing and/or the audio data is sent to a speech processing system to determine a responsive action to be performed by the device. When the entire wakeword is not detected, on-device processing is canceled and the device refrains from sending the audio data to the speech processing system.
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公开(公告)号：US10510340B1
公开(公告)日：2019-12-17
申请号：US15832331
申请日：2017-12-05
Applicant: Amazon Technologies, Inc.
Inventor： Gengshen Fu , Shiv Naga Prasad Vitaladevuni , Paul McIntyre , Shuang Wu
Abstract: Techniques for using a dynamic wakeword detection threshold are described. A server(s) may receive audio data corresponding to an utterance from a device in response to the device detecting a wakeword using a wakeword detection threshold. The server(s) may then determine the device should use a lower wakeword detection threshold for a duration of time. In addition to sending the device output data responsive to the utterance, the server(s) may send the device an instruction to use the lower wakeword detection threshold for the duration of time. Alternatively, the server(s) may train a machine learning model to determine when the device should use a lower wakeword detection threshold. The server(s) may send the trained machine learned model to the device for use at runtime.
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公开(公告)号：US11699433B2
公开(公告)日：2023-07-11
申请号：US16936952
申请日：2020-07-23
Applicant: Amazon Technologies, Inc.
Inventor： Gengshen Fu , Shiv Naga Prasad Vitaladevuni , Paul McIntyre , Shuang Wu
CPC classification number: G10L15/18 , G10L15/22 , G10L15/30 , G10L2015/088
Abstract: Techniques for using a dynamic wakeword detection threshold are described. A device detects a wakeword in audio data using a first wakeword detection threshold value. Thereafter, the device receives audio including speech. If the device receives the audio within a predetermined duration of time after detecting the previous wakeword, the device attempts to detect a wakeword in second audio data, corresponding to the audio including the speech, using a second, lower wakeword detection threshold value.
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公开(公告)号：US11205420B1
公开(公告)日：2021-12-21
申请号：US16436562
申请日：2019-06-10
Applicant: Amazon Technologies, Inc.
Inventor： Gengshen Fu , Thibaud Senechal , Shiv Naga Prasad Vitaladevuni , Michael J. Rodehorst , Varun K. Nagaraja
Abstract: A system and method performs wakeword detection using a neural network model that includes a recurrent neural network (RNN) for processing variable-length wakewords. To prevent the model from being influenced by non-wakeword speech, multiple instances of the model are created to process audio data, and each instance is configured to use weights determined by training data. The model may instead or in addition be used to process the audio data only when a likelihood that the audio data corresponds to the wakeword is greater than a threshold. The model may process the audio data as represented by groups of acoustic feature vectors; computations for feature vectors common to different groups may be re-used.
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