-
公开(公告)号：US10937413B2
公开(公告)日：2021-03-02
申请号：US16139891
申请日：2018-09-24
Applicant: Amazon Technologies, Inc.
Inventor： Jonathan B. Feinstein , Alok Verma , Amina Shabbeer , Brandon Scott Durham , Catherine Breslin , Edward Bueche , Fabian Moerchen , Fabian Triefenbach , Klaus Reiter , Toby R. Latin-Stoermer , Panagiota Karanasou , Judith Gaspers
Abstract: Techniques are provided for training a target language model based at least in part on data associated with a reference language model. For example, language data utilized to train an English language model may be translated and provided as training data to train a German language model to recognize utterances provided in German. By utilizing the techniques herein, the efficiency of training a new language model may be improved due at least in part to replacing labor-intensive operations conventionally performed by specialized personnel with machine-generated data. Additionally, techniques discussed herein provide for reducing the time required for training a new language model by leveraging information associated with utterances of one language to train the new language model associated with a different language.
-
Patent Agency Ranking
公开(公告)号：US20200098352A1
公开(公告)日：2020-03-26
申请号：US16139891
申请日：2018-09-24
Applicant: Amazon Technologies, Inc.
Inventor： Jonathan B. Feinstein , Alok Verma , Amina Shabbeer , Brandon Scott Durham , Catherine Breslin , Edward Bueche , Fabian Moerchen , Fabian Triefenbach , Klaus Reiter , Toby R. Latin-Stoermer , Panagiota Karanasou , Judith Gaspers
Abstract: Techniques are provided for training a target language model based at least in part on data associated with a reference language model. For example, language data utilized to train an English language model may be translated and provided as training data to train a German language model to recognize utterances provided in German. By utilizing the techniques herein, the efficiency of training a new language model may be improved due at least in part to replacing labor-intensive operations conventionally performed by specialized personnel with machine-generated data. Additionally, techniques discussed herein provide for reducing the time required for training a new language model by leveraging information associated with utterances of one language to train the new language model associated with a different language.
-
公开(公告)号：US10854189B2
公开(公告)日：2020-12-01
申请号：US16139984
申请日：2018-09-24
Applicant: Amazon Technologies, Inc.
Inventor： Jonathan B. Feinstein , Alok Verma , Amina Shabbeer , Brandon Scott Durham , Catherine Breslin , Edward Bueche , Fabian Moerchen , Fabian Triefenbach , Klaus Reiter , Toby R. Latin-Stoermer , Panagiota Karanasou , Judith Gaspers
Abstract: Techniques are provided for training a language recognition model. For example, a language recognition model may be maintained and associated with a reference language (e.g., English). The language recognition model may be configured to accept as input an utterance in the reference language and to identify a feature to be executed in response to receiving the utterance. New language data (e.g., other utterances) provided in a different language (e.g., German) may be obtained. This new language data may be translated to English and utilized to retrain the model to recognize reference language data as well as language data translated to the reference language. Subsequent utterances (e.g., English utterances, or German utterances translated to English) may be provided to the updated model and a feature may be identified. One or more instructions may be sent to a user device to execute a set of instructions associated with the feature.
-
公开(公告)号：US20200098351A1
公开(公告)日：2020-03-26
申请号：US16139984
申请日：2018-09-24
Applicant: Amazon Technologies, Inc.
Inventor： Jonathan B. Feinstein , Alok Verma , Amina Shabbeer , Brandon Scott Durham , Catherine Breslin , Edward Bueche , Fabian Moerchen , Fabian Triefenbach , Klaus Reiter , Toby R. Latin-Stoermer , Panagiota Karanasou , Judith Gaspers
Abstract: Techniques are provided for training a language recognition model. For example, a language recognition model may be maintained and associated with a reference language (e.g., English). The language recognition model may be configured to accept as input an utterance in the reference language and to identify a feature to be executed in response to receiving the utterance. New language data (e.g., other utterances) provided in a different language (e.g., German) may be obtained. This new language data may be translated to English and utilized to retrain the model to recognize reference language data as well as language data translated to the reference language. Subsequent utterances (e.g., English utterances, or German utterances translated to English) may be provided to the updated model and a feature may be identified. One or more instructions may be sent to a user device to execute a set of instructions associated with the feature.
-
公开(公告)号：US09400996B2
公开(公告)日：2016-07-26
申请号：US14311833
申请日：2014-06-23
Applicant: Amazon Technologies, Inc.
Inventor： Toby R. Latin-Stoermer , Abhoy Bhaktwatsalam , Randy C. Chung , Chi Ming Kan
CPC classification number: G06Q30/0643 , G06F17/30256 , G06K9/6202 , G06Q30/0633 , G06T7/0002 , Y10S707/948 , Y10S707/962
Abstract: Systems and methods for collecting, selecting, and displaying an image or image set in a network based environment are described. The systems and methods can collect multiple images for any given item from multiple sources, select a desired image (or set of images) that best depicts that item, and then display that selected image (or image set) in the network based environment. The desired image (or image set) that best depicts the item can be selected using any number or combination of pre-selected criteria. By using the pre-selected criteria, the process needs no manual intervention, and can therefore be automated or semi-automated to save both time and cost.
Abstract translation: 描述用于在基于网络的环境中收集，选择和显示图像或图像集的系统和方法。 系统和方法可以从多个来源收集任何给定项目的多个图像，选择最佳描绘该项目的所需图像（或图像集合），然后在基于网络的环境中显示所选图像（或图像集）。 可以使用任何数量或预先选择的标准组合来选择最能描绘物品的所需图像（或图像集）。 通过使用预先选择的标准，该过程不需要人工干预，因此可以自动化或半自动化以节省时间和成本。
-
公开(公告)号：US20150016727A1
公开(公告)日：2015-01-15
申请号：US14311833
申请日：2014-06-23
Applicant: Amazon Technologies, Inc.
Inventor： Toby R. Latin-Stoermer , Abhoy Bhaktwatsalam , Randy C. Chung , Chi Ming Kan
CPC classification number: G06Q30/0643 , G06F17/30256 , G06K9/6202 , G06Q30/0633 , G06T7/0002 , Y10S707/948 , Y10S707/962
Abstract: Systems and methods for collecting, selecting, and displaying an image or image set in a network based environment are described. The systems and methods can collect multiple images for any given item from multiple sources, select a desired image (or set of images) that best depicts that item, and then display that selected image (or image set) in the network based environment. The desired image (or image set) that best depicts the item can be selected using any number or combination of pre-selected criteria. By using the pre-selected criteria, the process needs no manual intervention, and can therefore be automated or semi-automated to save both time and cost.
Abstract translation: 描述用于在基于网络的环境中收集，选择和显示图像或图像集的系统和方法。 系统和方法可以从多个来源收集任何给定项目的多个图像，选择最佳描绘该项目的所需图像（或图像集合），然后在基于网络的环境中显示所选图像（或图像集）。 可以使用任何数量或预先选择的标准组合来选择最能描绘物品的所需图像（或图像集）。 通过使用预先选择的标准，该过程不需要人工干预，因此可以自动化或半自动化以节省时间和成本。
-
-
-
-
-
Search Results
6
records
(took 0.024 seconds)
