SYSTEMS AND METHODS FOR PROVIDING VOICE COMMAND RECOMMENDATIONS

    公开(公告)号:US20230260514A1

    公开(公告)日:2023-08-17

    申请号:US18139771

    申请日:2023-04-26

    Abstract: The system provides a voice command recommendation to a user to avoid a non-voice command. The system determines a command that is expected to be received, and generates a voice command recommendation that corresponds to the predicted command. The predicted command can be based on the user's behavior, a plurality of users' behavior, environmental circumstances such as a phone call ring, or a combination thereof. The system may access one or more databases to determine the predicted command. The voice command recommendation may include a displayed notification that describes the recommended voice command, and exemplary voice inputs that are recognized. The system also activates an audio interface, such as a microphone, that is configured to receive a voice input. If the system receives a recognizable voice input at the audio interface that corresponds to the recommendation, the system performs the predicted command in response to receiving the voice input.

    SYSTEMS AND METHODS FOR IMPROVING CONTENT DISCOVERY IN RESPONSE TO A VOICE QUERY

    公开(公告)号:US20230206904A1

    公开(公告)日:2023-06-29

    申请号:US18116501

    申请日:2023-03-02

    CPC classification number: G10L15/02 G06F16/433 G06F16/438 G06F40/279 G10L15/26

    Abstract: A transcription of a query for content discovery is generated, and a context of the query is identified, as well as a first plurality of candidate entities to which the query refers. A search is performed based on the context of the query and the first plurality of candidate entities, and results are generated for output. A transcription of a second voice query is then generated, and it is determined whether the second transcription includes a trigger term indicating a corrective query. If so, the context of the first query is retrieved. A second term of the second query similar to a term of the first query is identified, and a second plurality of candidate entities to which the second term refers is determined. A second search is performed based on the second plurality of candidates and the context, and new search results are generated for output.

    METHOD AND APPARATUS FOR GENERATING HINT WORDS FOR AUTOMATED SPEECH RECOGNITION

    公开(公告)号:US20230146333A1

    公开(公告)日:2023-05-11

    申请号:US17984479

    申请日:2022-11-10

    CPC classification number: G10L15/02 G10L15/22 G10L2015/025 G10L2015/223

    Abstract: Systems and methods for determining hint words that improve the accuracy of automated speech recognition (ASR) systems. Hint words are determined in the context of a user issuing voice commands in connection with a voice interface system. Terms are initially taken from most frequently occurring terms in operation of a voice interface system. For example, most frequently occurring terms that arise in electronic search queries or received commands are selected. Certain of these terms are selected as hint words, and the selected hint words are then transmitted to an ASR system to assist in translation of speech to text.

    SYSTEM AND METHOD FOR SELECTION OF SUPPLEMENTAL CONTENT ACCORDING TO SKIP LIKELIHOOD

    公开(公告)号:US20230110586A1

    公开(公告)日:2023-04-13

    申请号:US17500417

    申请日:2021-10-13

    Abstract: Systems and methods for a computer-based process that determines when a viewer is likely to skip over supplemental content and adjusts supplemental content presentation to compensate. Systems of embodiments of the disclosure may utilize various inputs to determine the likelihood of skipping supplemental content, including cursor position at or near specified icons or other UI elements, as well as user actions such as gaze direction, various motions or actions, controller manipulations, and the like. Once a likelihood of skipping supplemental content is determined, various actions may be taken in response, including without limitation selection of supplemental content that conveys its intended message prior to skipping, supplemental content that can be played at increased speed, and designation of supplemental content slots as skippable or non-skippable.

    Methods for natural language model training in natural language understanding (NLU) systems

    公开(公告)号:US11626103B2

    公开(公告)日:2023-04-11

    申请号:US16805342

    申请日:2020-02-28

    Abstract: Systems and methods for determining to perform an action of a query using a trained natural language model of a natural language understanding (NLU) system are disclosed herein. A text string corresponding to a prescribed action includes at least a content entity is received. A determination is made as to whether the text string corresponds to an audio input of a first group. In response to determining the text string corresponds to an audio input of a first group, a determination is made as to whether the text string includes an obsequious expression. In response to determining the text string corresponds to an audio input of a first group and in response to determining the text string includes an obsequious expression, a determination is made to perform the prescribed action. In response to determining the text string corresponds to an audio input of a first group and in response to determining the text string does not include the obsequious expression, a determination is made to not perform the prescribed action.

    INCREASING USER ENGAGEMENT THROUGH QUERY SUGGESTION

    公开(公告)号:US20230022515A1

    公开(公告)日:2023-01-26

    申请号:US17381908

    申请日:2021-07-21

    Abstract: Systems and methods are presented herein for increasing user engagement with an interface by suggesting commands or queries for the user. A plurality of content items available for consumption are identified and metadata for each of the plurality of content items is retrieved. One or more candidate voice commands are generated based on a plurality of voice command templates based on a target verb and a subset of the metadata corresponding to the plurality of the content items available for consumption. A recall score is generated for each candidate voice command based at least in part on a detection of phonetic features that match between clauses of each candidate voice command. At least the candidate voice command with the highest recall score is selected and output using a suggestion system.

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