利索-全球专利检索

  1. 登录
  2. 注册

搜索结果

8399 条记录 (耗时 0.031 秒)

    System And Method For Determining An Intent Of A User From An Utterance Of The User
    5.
    发明公开
    System And Method For Determining An Intent Of A User From An Utterance Of The User 审中-公开

    公开(公告)号：US20240347052A1

    公开(公告)日：2024-10-17

    申请号：US18299462

    申请日：2023-04-12

    申请人： Ubona Technologies Private Limited

    发明人： Nimesh SINHA ,  Abhi DATTASHARMA ,  Amit GHOSH

    IPC分类号： G10L15/18 ,  G10L15/197 ,  G10L15/22 ,  G10L15/30

    CPC分类号： G10L15/1815 ,  G10L15/197 ,  G10L15/22 ,  G10L15/30

    摘要： Disclosed is a system and method for determining an intent of a user from an utterance of the user. The system initially builds an intent determination model using a plurality of sample utterances, each assigned with at least one intent class. That is, on receiving the sample utterances, the system extracts significant word pairs from each sample utterance, computes a distinction factor of each significant word pairs, computes a Positive Probability and a Negative Probability for each significant word pairs, and generates the intent determination model by storing each significant word pairs and its distinction factor, the Positive Probability and the Negative Probability. Then on receiving any new utterance, the system extracts significant word pairs, identifies one or more matching word pairs in the model and determines the intent of based on the distinction factor, Positive Probability, and the Negative Probability of the one or more matched word pairs.

    Object tracking and entity resolution
    6.
    发明授权
    Object tracking and entity resolution 有权

    公开(公告)号：US12117838B1

    公开(公告)日：2024-10-15

    申请号：US17218621

    申请日：2021-03-31

    申请人： Amazon Technologies, Inc.

    发明人： Gunnar Atli Sigurdsson ,  Robinson Piramuthu ,  Gokhan Tur

    IPC分类号： G06T7/70 ,  G05D1/00 ,  G05D1/02 ,  G06T7/73 ,  G10L13/08 ,  G10L15/18 ,  G10L15/22

    CPC分类号： G05D1/0219 ,  G05D1/0088 ,  G05D1/0251 ,  G05D1/0274 ,  G06T7/73 ,  G10L13/08 ,  G10L15/1807 ,  G10L15/22 ,  G10L2015/223

    摘要： Described herein is a system for tracking objects and performing dynamic entity resolution using image data. For example, the system may build an environment map and populate the map with objects present in the environment. As the devices move about the environment it may capture image data and, based on its position and/or configuration of its components, may determine updated locations of objects that move in the environment. Upon receiving a query from a user, based on the location of the objects relative to the device/user, the system can interpret gestures and voice commands to infer which object is specified by the voice command. To build the environment map, the system performs object detection to generate bounding boxes associated with an object, then clusters the bounding boxes into a three-dimensional (3D) object associated with 3D coordinates. As the system tracks the object using the 3D coordinates while maintaining two-dimensional (2D) information (e.g., bounding boxes and other features), the system can use existing 2D models to process objects in 3D.

    RELEVANT CONTEXT DETERMINATION
    10.
    发明公开
    RELEVANT CONTEXT DETERMINATION 审中-公开

    公开(公告)号：US20240331686A1

    公开(公告)日：2024-10-03

    申请号：US18739466

    申请日：2024-06-11

    申请人： Amazon Technologies, Inc.

    发明人： Kai Wei ,  Thanh Dac Tran ,  Grant Strimel

    IPC分类号： G10L15/18 ,  G06N3/08 ,  G10L15/06 ,  G10L15/16 ,  G10L15/22 ,  G10L15/28

    CPC分类号： G10L15/1815 ,  G06N3/08 ,  G10L15/063 ,  G10L15/16 ,  G10L15/22 ,  G10L15/28 ,  G10L2015/228

    摘要： Techniques for determining and storing relevant context information for a user input, such as a spoken input, are described. In some embodiments, context information is determined to be relevant on an audio frame basis. Context scores for different types of context data (e.g., prior dialog turn data, user profile data, device information, etc.) are determined for individual audio frames corresponding to a spoken input. Based on the corresponding context scores, the most relevant context is stored in a local context cache. The local context cache is updated as subsequent audio frames, of the user input, are processed. The data stored in the context cache is provided to downstream components to perform tasks such as ASR, NLU and SLU.