Transforming audio content into images

    公开(公告)号:US10891969B2

    公开(公告)日:2021-01-12

    申请号:US16165281

    申请日:2018-10-19

    Abstract: A technique is described herein for transforming audio content into images. The technique may include: receiving the audio content from a source; converting the audio content into a temporal stream of audio features; and converting the stream of audio features into one or more images using one or more machine-trained models. The technique generates the image(s) based on recognition of: semantic information that conveys one or more semantic topics associated with the audio content; and sentiment information that conveys one or more sentiments associated with the audio content. The technique then generates an output presentation that includes the image(s), which it provides to one or more display devices for display thereat. The output presentation serves as a summary of salient semantic and sentiment-related characteristics of the audio content.

    Visual search services for multiple partners

    公开(公告)号:US12299029B2

    公开(公告)日:2025-05-13

    申请号:US15888960

    申请日:2018-02-05

    Abstract: Systems and methods can be implemented to conduct a visual search as a service in a variety of applications. In various embodiments, a system is configured to provide searching capabilities of content provided by a first entity in response to a search request by a second entity. An image provided by the second entity can be used by the system as a query image to search the content of the first entity. In an embodiment, the first entity can be a commercial entity providing such a system with image related content regarding its products and services such that any number of individual consumers can search for particular products and services of the commercial entity via their communication enabled devices. In addition, such systems can be arranged for other embodiments to provide customized searches of a single source by many individual devices. Additional systems and methods are disclosed.

    VISUAL INTENT TRIGGERING FOR VISUAL SEARCH
    16.
    发明申请

    公开(公告)号:US20200019628A1

    公开(公告)日:2020-01-16

    申请号:US16036224

    申请日:2018-07-16

    Abstract: Representative embodiments disclose mechanisms to perform visual intent classification or visual intent detection or both on an image. Visual intent classification utilizes a trained machine learning model that classifies subjects in the image according to a classification taxonomy. The visual intent classification can be used as a pre-triggering mechanism to initiate further action in order to substantially save processing time. Example further actions include user scenarios, query formulation, user experience enhancement, and so forth. Visual intent detection utilizes a trained machine learning model to identify subjects in an image, place a bounding box around the image, and classify the subject according to the taxonomy. The trained machine learning model utilizes multiple feature detectors, multi-layer predictions, multilabel classifiers, and bounding box regression.

    METHOD AND APPARATUS FOR GENERATING VISUAL SEARCH QUERIES AUGMENTED BY SPEECH INTENT

    公开(公告)号:US20190311070A1

    公开(公告)日:2019-10-10

    申请号:US15947564

    申请日:2018-04-06

    Abstract: A method for using a speech signal to augment a visual search includes processing the image data to determine an image search intent. Concurrently with processing the image data, the method processes the speech signal to determine at least one speech search intent. The method generates a search query by combining keywords and/or the image from the image search intent with keywords from the speech search intent. The method then performs a search based on the generated query and reports the results of the search. The method generates the image search intent by applying the image data to a knowledge base and generates the speech search intent by converting the speech to text and applying the text to a cognition service.

    MACHINE LEARNING HYPERPARAMETER TUNING TOOL
    18.
    发明申请

    公开(公告)号:US20190236487A1

    公开(公告)日:2019-08-01

    申请号:US15883686

    申请日:2018-01-30

    CPC classification number: G06N20/00 G06F3/04842

    Abstract: A technique for hyperparameter tuning can be performed via a hyperparameter tuning tool. In the technique, computer-readable values for each of one or more machine learning hyperparameters can be received. Multiple computer-readable hyperparameter value sets can be defined using different combinations of the values. In response to a request to start, an overall hyperparameter tuning operation can be performed via the tool, with the overall operation including a tuning job for each of the hyperparameter sets. A computer-readable comparison of the results of the parameter tuning operations can be generated for the hyperparameter sets, with the comparison indicating effectiveness of the hyperparameter sets, as compared to each other, in the tuning jobs.

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