Efficient generation of personalized spoken language understanding models

    公开(公告)号:US10109273B1

    公开(公告)日:2018-10-23

    申请号:US14014154

    申请日:2013-08-29

    Abstract: Features are disclosed for maintaining data that can be used to personalize spoken language understanding models, such as speech recognition or natural language understanding models. The personalization data can be used to update the models based on some or all of the data. The data may be obtained from various data sources, such as applications or services used by the user. Personalized spoken language understanding models may be generated or updated based on updates to the personalization data or some other portion of the stored personalization data. Generation of personalized spoken language understanding models may be prioritized such that the generation process accommodates multiple users.

    GAZE INITIATED ACTIONS
    5.
    发明申请

    公开(公告)号:US20250004544A1

    公开(公告)日:2025-01-02

    申请号:US18344921

    申请日:2023-06-30

    Abstract: A system that detects the location of a user gaze at a display and in response to the duration of the gaze exceeding a threshold, auto-playing content on the display. The system may also determine gaze event data associating the gaze event with the source of the content the user is gazing at. Other information may also be associated with the gaze event such as user ID, time/duration data, or the like. Various actions can be taken in response to the gaze event such as auto-playing of content, outputting a visual indication of the detected gaze, interpreting detected speech using the gaze event data, data aggregation, etc.

    Speech recognition capability generation and control
    6.
    发明授权
    Speech recognition capability generation and control 有权
    语音识别能力的生成与控制

    公开(公告)号:US09443527B1

    公开(公告)日:2016-09-13

    申请号:US14040011

    申请日:2013-09-27

    Abstract: A system for controlling multiple devices using automatic speech recognition (ASR) even when the devices may not be capable of performing ASR themselves. A device such as a media player, appliance, or the like may be recognized by a network. The configured controls for the device (such as a remote control or other mechanism) are incorporated into a device control registry which catalogs device command controls. Individual ASR grammars are constructed for the devices so speech commands for those devices may be processed by an ASR device. The ASR device may then process those speech commands and convert them into the appropriate inputs for the controlled device. The inputs may then be sent to the controlled device, resulting in ASR control for non-ASR devices.

    Abstract translation: 即使设备可能无法执行ASR本身,也可以使用自动语音识别(ASR)来控制多个设备的系统。 诸如媒体播放器,设备等的设备可被网络识别。 设备的配置控件(如远程控制或其他机制)被合并到设备控制注册表中,该设备控制注册表编制设备命令控件。 为设备构建单独的ASR语法,因此这些设备的语音命令可能由ASR设备进行处理。 然后,ASR设备可以处理那些语音命令,并将它们转换为受控设备的适当输入。 然后可以将输入发送到受控设备,导致非ASR设备的ASR控制。

    Retrieval and management of spoken language understanding personalization data
    7.
    发明授权
    Retrieval and management of spoken language understanding personalization data 有权
    口语理解个性化数据的检索和管理

    公开(公告)号:US09361289B1

    公开(公告)日:2016-06-07

    申请号:US14015697

    申请日:2013-08-30

    CPC classification number: G10L15/18 G06F17/30684 G10L15/07

    Abstract: Features are disclosed for maintaining data that can be used to personalize spoken language processing, such as automatic speech recognition (“ASR”), natural language understanding (“NLU”), natural language processing (“NLP”), etc. The data may be obtained from various data sources, such as applications or services used by the user. User-specific data maintained by the data sources can be retrieved and stored for use in generating personal models. Updates to data at the data sources may be reflected by separate data sets in the personalization data, such that other processes can obtain the update data sets separate from other data.

    Abstract translation: 公开了用于维护可用于个性化口语处理的数据的特征,例如自动语音识别(“ASR”),自然语言理解(“NLU”),自然语言处理(“NLP”)等。数据可以 可以从各种数据源获得,例如用户使用的应用程序或服务。 可以检索和存储由数据源维护的用户特定数据,以用于生成个人模型。 数据源上的数据更新可以通过个性化数据中的单独的数据集来反映,使得其他进程可以获得与其他数据分离的更新数据集。

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