公开(公告)号：US20150332672A1

公开(公告)日：2015-11-19

申请号：US14280070

申请日：2014-05-16

申请人： Microsoft Corporation

发明人： Murat Akbacak ,  Dilek Z. Hakkani-Tur ,  Gokhan Tur ,  Larry P. Heck ,  Benoit Dumoulin

IPC分类号： G10L15/18

CPC分类号： G10L15/18 ,  G06F17/30654 ,  G06F17/30734 ,  G06F17/30766 ,  G10L15/07

摘要： Systems and methods are provided for improving language models for speech recognition by personalizing knowledge sources utilized by the language models to specific users or user-population characteristics. A knowledge source, such as a knowledge graph, is personalized for a particular user by mapping entities or user actions from usage history for the user, such as query logs, to the knowledge source. The personalized knowledge source may be used to build a personal language model by training a language model with queries corresponding to entities or entity pairs that appear in usage history. In some embodiments, a personalized knowledge source for a specific user can be extended based on personalized knowledge sources of similar users.

摘要翻译： 提供了系统和方法，用于通过将语言模型所使用的知识源个性化为特定用户或用户群体特征来改进用于语音识别的语言模型。 通过将实体或用户操作与用户的使用历史（例如查询日志）映射到知识源，为特定用户个性化知识源。 个性化知识源可以用于通过训练具有与出现在使用历史中的实体或实体对相对应的查询的语言模型来构建个人语言模型。 在一些实施例中，可以基于类似用户的个性化知识源来扩展用于特定用户的个性化知识源。

公开(公告)号：US09679558B2

公开(公告)日：2017-06-13

申请号：US14278659

申请日：2014-05-15

申请人： Microsoft Corporation

发明人： Murat Akbacak ,  Dilek Z. Hakkani-Tur ,  Gokhan Tur ,  Larry P. Heck ,  Benoit Dumoulin

IPC分类号： G10L15/22 ,  G10L15/06 ,  G06F17/28 ,  G10L15/18 ,  G06F17/30 ,  G10L15/183

CPC分类号： G10L15/063 ,  G06F17/28 ,  G06F17/30654 ,  G06F17/30766 ,  G10L15/18 ,  G10L15/183

摘要： Systems and methods are provided for training language models using in-domain-like data collected automatically from one or more data sources. The data sources (such as text data or user-interactional data) are mined for specific types of data, including data related to style, content, and probability of relevance, which are then used for language model training. In one embodiment, a language model is trained from features extracted from a knowledge graph modified into a probabilistic graph, where entity popularities are represented and the popularity information is obtained from data sources related to the knowledge. Embodiments of language models trained from this data are particularly suitable for domain-specific conversational understanding tasks where natural language is used, such as user interaction with a game console or a personal assistant application on personal device.

公开(公告)号：US20150278191A1

公开(公告)日：2015-10-01

申请号：US14227492

申请日：2014-03-27

申请人： Microsoft Corporation

发明人： Michael Levit ,  Hernan Guelman ,  Shuangyu Chang ,  Sarangarajan Parthasarathy ,  Benoit Dumoulin

IPC分类号： G06F17/27

CPC分类号： G10L15/183 ,  G06F17/2755 ,  G06F17/2785 ,  G10L15/30

摘要： The customization of language modeling components for speech recognition is provided. A list of language modeling components may be made available by a computing device. A hint may then be sent to a recognition service provider for combining the multiple language modeling components from the list. The hint may be based on a number of different domains. A customized combination of the language modeling components based on the hint may then be received from the recognition service provider.

摘要翻译： 提供了用于语音识别的语言建模组件的定制。 语言建模组件的列表可以由计算设备提供。 然后，可以向识别服务提供商发送提示，以从列表中组合多个语言建模组件。 提示可能基于许多不同的域。 然后可以从识别服务提供商接收基于提示的语言建模组件的定制组合。

公开(公告)号：US20140188956A1

公开(公告)日：2014-07-03

申请号：US13730815

申请日：2012-12-28

申请人： MICROSOFT CORPORATION

发明人： Rajen Subba ,  Dragomir Yankov ,  Pavel Berkhin ,  Steven William Macbeth ,  Zhaowei Charlie Jiang ,  Benoit Dumoulin

IPC分类号： G06F17/30

CPC分类号： G06F16/185 ,  G06F9/453

摘要： Content is proactively presented to a user, to enable the user to more efficiently access such content. A user context is correlated to content that is likely to be subsequently accessed. One such a correlation is specific to a given user, while another such correlation is general to a collection, or class, of users. Correlations between a current user context and content subsequently accessed are based on historical data and are defined in terms of mathematical functions or semantic relationships. Such correlations are then utilized to identify content that is likely to be subsequently accessed, and such content is proactively presented to a user. A user interface provides a defined area within which proactive presentations of content are made, including while the user is utilizing other application programs.

摘要翻译： 将内容主动呈现给用户，以使用户能够更有效地访问这些内容。 用户上下文与可能随后访问的内容相关联。 一个这样的相关性对于给定的用户是特定的，而另一个这样的相关性对于用户的集合或类是通用的。 当前用户上下文和随后访问的内容之间的相关性基于历史数据，并且根据数学函数或语义关系定义。 然后利用这样的相关性来识别可能随后被访问的内容，并且这些内容被主动呈现给用户。 用户界面提供在其中进行内容的主动呈现的定义区域，包括当用户正在利用其他应用程序时。

公开(公告)号：US20150332670A1

公开(公告)日：2015-11-19

申请号：US14278659

申请日：2014-05-15

申请人： Microsoft Corporation

发明人： Murat Akbacak ,  Dilek Z. Hakkani-Tur ,  Gokhan Tur ,  Larry P. Heck ,  Benoit Dumoulin

IPC分类号： G10L15/06 ,  G10L15/18 ,  G06F17/28

CPC分类号： G10L15/063 ,  G06F17/28 ,  G06F17/30654 ,  G06F17/30766 ,  G10L15/18 ,  G10L15/183

摘要： Systems and methods are provided for training language models using in-domain-like data collected automatically from one or more data sources. The data sources (such as text data or user-interactional data) are mined for specific types of data, including data related to style, content, and probability of relevance, which are then used for language model training. In one embodiment, a language model is trained from features extracted from a knowledge graph modified into a probabilistic graph, where entity popularities are represented and the popularity information is obtained from data sources related to the knowledge. Embodiments of language models trained from this data are particularly suitable for domain-specific conversational understanding tasks where natural language is used, such as user interaction with a game console or a personal assistant application on personal device.

摘要翻译： 提供了系统和方法，用于使用从一个或多个数据源自动收集的类似域的数据来训练语言模型。 为特定类型的数据挖掘数据源（如文本数据或用户交互数据），包括与风格，内容和相关概率相关的数据，然后将其用于语言模型培训。 在一个实施例中，从从修改为概率图的知识图中提取的特征来训练语言模型，其中表示实体流行度，并且从与知识相关的数据源获得流行度信息。 从该数据训练的语言模型的实施例特别适用于使用自然语言的领域特定对话理解任务，例如用户与个人设备上的游戏控制台或个人助理应用程序的交互。

公开(公告)号：US20150269949A1

公开(公告)日：2015-09-24

申请号：US14219642

申请日：2014-03-19

申请人： MICROSOFT CORPORATION

发明人： Shuangyu Chang ,  Michael Levit ,  Abhik Lahiri ,  Barlas Oguz ,  Benoit Dumoulin

IPC分类号： G10L19/005

CPC分类号： G10L15/32 ,  G10L15/063 ,  G10L15/14 ,  G10L19/005

摘要： An incremental speech recognition system. The incremental speech recognition system incrementally decodes a spoken utterance using an additional utterance decoder only when the additional utterance decoder is likely to add significant benefit to the combined result. The available utterance decoders are ordered in a series based on accuracy, performance, diversity, and other factors. A recognition management engine coordinates decoding of the spoken utterance by the series of utterance decoders, combines the decoded utterances, and determines whether additional processing is likely to significantly improve the recognition result. If so, the recognition management engine engages the next utterance decoder and the cycle continues. If the accuracy cannot be significantly improved, the result is accepted and decoding stops. Accordingly, a decoded utterance with accuracy approaching the maximum for the series is obtained without decoding the spoken utterance using all utterance decoders in the series, thereby minimizing resource usage.

摘要翻译： 增量语音识别系统。 只有当附加话语解码器可能对组合结果增加显着的益处时，增量语音识别系统才会使用附加话音解码器递增地解码语音话语。 可用的话语解码器是基于准确性，性能，多样性等因素进行排序的。 识别管理引擎通过一系列话音解码器来协调语音发音的解码，组合解码的话语，并确定附加处理是否可能显着改善识别结果。 如果是这样，识别管理引擎接合下一个话音解码器，并且该周期继续。 如果精度无法显着提高，结果被接受，解码停止。 因此，在使用系列中的所有话语解码器对语音发音进行解码的情况下，获得具有接近该系列的最大值的精确解码语音，从而最小化资源使用。

公开(公告)号：US09997157B2

公开(公告)日：2018-06-12

申请号：US14280070

申请日：2014-05-16

申请人： Microsoft Corporation

发明人： Murat Akbacak ,  Dilek Z. Hakkani-Tur ,  Gokhan Tur ,  Larry P. Heck ,  Benoit Dumoulin

IPC分类号： G06F17/30 ,  G10L15/06 ,  G10L15/18 ,  G10L15/07

CPC分类号： G10L15/18 ,  G06F17/30654 ,  G06F17/30734 ,  G06F17/30766 ,  G10L15/07

摘要： Systems and methods are provided for improving language models for speech recognition by personalizing knowledge sources utilized by the language models to specific users or user-population characteristics. A knowledge source, such as a knowledge graph, is personalized for a particular user by mapping entities or user actions from usage history for the user, such as query logs, to the knowledge source. The personalized knowledge source may be used to build a personal language model by training a language model with queries corresponding to entities or entity pairs that appear in usage history. In some embodiments, a personalized knowledge source for a specific user can be extended based on personalized knowledge sources of similar users.

公开(公告)号：US20150046418A1

公开(公告)日：2015-02-12

申请号：US13963443

申请日：2013-08-09

申请人： Microsoft Corporation

发明人： Murat Akbacak ,  Benoit Dumoulin

IPC分类号： G06F17/30

CPC分类号： G06F16/48 ,  G06F16/41 ,  G06F16/907

摘要： One or more techniques and/or systems are provided for maintaining user tagged content. For example, a user may experience content (e.g., watch a scene of a movie, create a photo, create a social network post, read an email, etc.), which the user may desire to save and/or organize for later retrieval. Accordingly, a personalization tag for the content may be received from the user (e.g., “Paris vacation photo”). The content may be indexed with the personalization tag within a personalization index (e.g., a cloud-based index for the user that may be accessible to any device associated with the user). In this way, the user may retrieve the content at a later point in time from any device. For example, a search query “Paris photos” may be received from the user. The personalization index may be queried using the search query to identify content that may be provided to the user.

摘要翻译： 提供一个或多个技术和/或系统来维护用户标记的内容。 例如，用户可以体验内容（例如，观看电影的场景，创建照片，创建社交网络帖子，读取电子邮件等），用户可能希望保存和/或组织以供稍后检索 。 因此，可以从用户（例如，“巴黎假期照片”）接收用于内容的个性化标签。 可以在个性化索引（例如，对于与用户相关联的任何设备可访问的用户的基于云的索引）中的个性化标签来索引内容。 以这种方式，用户可以在任何设备的稍后时间点检索内容。 例如，可以从用户接收到搜索查询“巴黎照片”。 可以使用搜索查询来查询个性化索引以识别可以提供给用户的内容。