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公开(公告)号：US09412361B1
公开(公告)日：2016-08-09
申请号：US14501562
申请日：2014-09-30
Applicant: Amazon Technologies, Inc.
Inventor： Alborz Geramifard , Sankaranarayanan Ananthakrishnan
IPC: G10L15/00 , G10L15/06 , G10L15/065 , G10L25/51 , G10L15/22
CPC classification number: G10L25/51 , G06K9/00691 , G06K9/6293 , G10L2015/223
Abstract: A system that configures a device's operation based on the device's environment. The system may receive scene data describing a scene in which the device will operate. The scene data may include image data, audio data, or other data. A feature vector comprising the scene data may be processed to identify one or more categories to be associated with the scene. Various processing techniques, such as using Bayesian nonparametric models, may be used to categorize the scene data. The device may then adjust its operation based on the one or more selected categories.
Abstract translation: 基于设备环境配置设备操作的系统。 系统可以接收描述设备将在其中操作的场景的场景数据。 场景数据可以包括图像数据，音频数据或其他数据。 可以处理包括场景数据的特征向量以识别要与场景相关联的一个或多个类别。 可以使用诸如使用贝叶斯非参数模型的各种处理技术来对场景数据进行分类。 然后，设备可以基于一个或多个所选择的类别来调整其操作。
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Patent Agency Ranking
公开(公告)号：US10854191B1
公开(公告)日：2020-12-01
申请号：US15710229
申请日：2017-09-20
Applicant: Amazon Technologies, Inc.
Inventor： Alborz Geramifard , Shiladitya Roy , Ruhi Sarikaya
Abstract: Techniques for optimizing a system to improve an overall user satisfaction in a speech controlled system are described. A user speaks an utterance and the system compares an expected sum of user satisfaction values for each action to make a decision as to how best to process the utterance. As a result, the system may make a decision that decreases user satisfaction in the short term but increases user satisfaction in the long term. The system may estimate a user satisfaction value and associate the estimated user satisfaction value with a current dialog state. By tracking user satisfaction values over time, the system may train machine learning models to optimize the expected sum of user satisfaction values. This improves how the system selects an action or application to which to dispatch the dialog state and how a specific application selects an action or intent corresponding to the command.
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公开(公告)号：US20240153489A1
公开(公告)日：2024-05-09
申请号：US18414530
申请日：2024-01-17
Applicant: Amazon Technologies, Inc.
Inventor： Alborz Geramifard , Shiladitya Roy , Ruhi Sarikaya
CPC classification number: G10L15/01 , G10L15/16 , G10L15/22 , G10L2015/225
Abstract: Techniques for optimizing a system to improve an overall user satisfaction in a speech controlled system are described. A user speaks an utterance and the system compares an expected sum of user satisfaction values for each action to make a decision as to how best to process the utterance. As a result, the system may make a decision that decreases user satisfaction in the short term but increases user satisfaction in the long term. The system may estimate a user satisfaction value and associate the estimated user satisfaction value with a current dialog state. By tracking user satisfaction values over time, the system may train machine learning models to optimize the expected sum of user satisfaction values. This improves how the system selects an action or application to which to dispatch the dialog state and how a specific application selects an action or intent corresponding to the command.
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公开(公告)号：US20210193116A1
公开(公告)日：2021-06-24
申请号：US17106395
申请日：2020-11-30
Applicant: Amazon Technologies, Inc.
Inventor： Alborz Geramifard , Shiladitya Roy , Ruhi Sarikaya
Abstract: Techniques for optimizing a system to improve an overall user satisfaction in a speech controlled system are described. A user speaks an utterance and the system compares an expected sum of user satisfaction values for each action to make a decision as to how best to process the utterance. As a result, the system may make a decision that decreases user satisfaction in the short term but increases user satisfaction in the long term. The system may estimate a user satisfaction value and associate the estimated user satisfaction value with a current dialog state. By tracking user satisfaction values over time, the system may train machine learning models to optimize the expected sum of user satisfaction values. This improves how the system selects an action or application to which to dispatch the dialog state and how a specific application selects an action or intent corresponding to the command.
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公开(公告)号：US10970774B1
公开(公告)日：2021-04-06
申请号：US14492638
申请日：2014-09-22
Applicant: Amazon Technologies, Inc.
Inventor： Alborz Geramifard , Hugh Evan Secker-Walker
Abstract: Provided are systems and methods for receiving a plurality of item submissions from a plurality of mobile user devices (each item submission of the plurality of item submissions including: item identifier data indicative of an item; and item location data indicative of a location of the item), determining a determined location for the item (using the respective item location data for each of the plurality of item submissions), and storing the determined location for the item in an item location database. The determined location for the item is stored in association with an item identifier corresponding to the item, and the item location database stores determined locations for a plurality of items.
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公开(公告)号：US09953652B1
公开(公告)日：2018-04-24
申请号：US14260094
申请日：2014-04-23
Applicant: Amazon Technologies, Inc.
Inventor： Delip Rao , Christian Darrel Monson , Alborz Geramifard
CPC classification number: G06F17/30634 , G06F17/30507 , G10L15/26
Abstract: Features are disclosed for processing user queries into a form that can produce relevant results. Spoken user queries can be transcribed into textual queries. Textual queries can be processed using a statistical model to identify entities within the queries. Running searches using the entities rather than the original search query can produce relevant results even when no result would have been obtained by running the original search query. In some embodiments, attributes may be identified and used during the search to narrow the results and potentially produce results that are more relevant.
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