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公开(公告)号：US20240104829A1
公开(公告)日：2024-03-28
申请号：US17935568
申请日：2022-09-26
Applicant: Sony Interactive Entertainment Inc.
Inventor： Sudha Krishnamurthy
IPC: G06T15/20
CPC classification number: G06T15/205 , G06T2200/04
Abstract: Deep learning techniques such as vector graphics are used to create 3D content and assets for metaverse applications. Vector graphics is a scalable format that provides rich 3D content. A vector graphics encoder such as a deep neural network such as a recurrent neural network (RNN) or transformer receives vector graphics and generates an encoded output. The encoded output is decoded by a 3D decoder such as another deep neural network that outputs 2D graphics for comparison with the original image. Loss is computed between the original and the output of the 3D decoder. The loss is back propagated to train the vector graphics encoder to generate 3D content.
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2.发明授权公开(公告)号：US11615312B2
公开(公告)日：2023-03-28
申请号：US16848499
申请日：2020-04-14
Applicant: Sony Interactive Entertainment Inc.
Inventor： Sudha Krishnamurthy
Abstract: An automated method, system, and computer readable medium for generating sound effect recommendations for visual input by training machine learning models that learn audio-visual correlations from a reference image or video, a positive audio signal, and a negative audio signal. A machine learning algorithm is used with a reference visual input, a positive audio signal input or a negative audio signal input to train a multimodal clustering neural network to output representations for the visual input and audio input as well as correlation scores between the audio and visual representations. The trained multimodal clustering neural network is configured to learn representations in such a way that the visual representation and positive audio representation have higher correlation scores than the visual representation and a negative audio representation or an unrelated audio representation.
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公开(公告)号：US11547938B2
公开(公告)日：2023-01-10
申请号：US17220743
申请日：2021-04-01
Applicant: Sony Interactive Entertainment Inc.
Inventor： David Nelson , Sudha Krishnamurthy , Mahdi Azmandian
Abstract: Methods and systems for representing emotions of an audience of spectators viewing online gaming of a video game include capturing interaction data from spectators of an audience engaged in watching gameplay of the video game. The captured interaction data is used to cluster the spectators into different groups in accordance to emotions detected from the interactions of spectators in the audience. A graphic interchange format file (GIF) is identified for each group based on the emotion associated with the group. The GIFs representing the distinct emotions of different groups of spectators are forwarded to client devices of spectators for rendering alongside content of the video game.
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公开(公告)号：US20220358718A1
公开(公告)日：2022-11-10
申请号：US17308023
申请日：2021-05-04
Applicant: Sony Interactive Entertainment Inc.
Inventor： Sudha Krishnamurthy , Michael Taylor
Abstract: A computer simulation object such as a chair is described by voice or photo input to render a 2D image. Machine learning may be used to convert voice input to the 2D image. The 2D image is converted to a 3D object and the 3D object or portions thereof are used in the computer simulation, such as a computer game, as the object such as a chair. A physics engine can be used to modify the 3D objects.
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公开(公告)号：US20220171960A1
公开(公告)日：2022-06-02
申请号：US17220739
申请日：2021-04-01
Applicant: Sony Interactive Entertainment Inc.
Inventor： David Nelson , Sudha Krishnamurthy , Mahdi Azmandian
IPC: G06K9/00 , A63F13/86 , A63F13/87 , H04N21/442 , H04N21/478 , H04N21/4788
Abstract: Methods and systems for representing emotions of an audience of spectators viewing online gaming of a video game include capturing interaction data from spectators of an audience engaged in watching gameplay of the video game. The captured interaction data is used to cluster the spectators into different groups in accordance to emotions detected from the interactions of spectators in the audience. A reaction track is identified for each group based on the emotion associated with the group. The reaction tracks representing distinct emotions of different groups of spectators are presented alongside content of the video game.
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Patent Agency Ranking
公开(公告)号：US10828566B2
公开(公告)日：2020-11-10
申请号：US16173755
申请日：2018-10-29
Applicant: SONY INTERACTIVE ENTERTAINMENT INC.
Inventor： Sudha Krishnamurthy
IPC: A63F13/67 , A63F13/5375 , A63F13/79 , A63F13/422
Abstract: A video game console, a video game system, and a computer-implemented method are described. Generally, a video game and video game assistance are adapted to a player. For example, a narrative of the video game is personalized to an experience level of the player. Similarly, assistance in interacting with a particular context of the video game is also personalized. The personalization learns from historical interactions of players with the video game and, optionally, other video games. In an example, a deep learning neural network is implemented to generate knowledge from the historical interactions. The personalization is set according to the knowledge.
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公开(公告)号：US20190341025A1
公开(公告)日：2019-11-07
申请号：US16383896
申请日：2019-04-15
Applicant: Sony Interactive Entertainment Inc.
Inventor： Masanori Omote , Ruxin Chen , Xavier Menendez-Pidal , Jaekwon Yoo , Koji Tashiro , Sudha Krishnamurthy , Komath Naveen Kumar
Abstract: A system and method for multimodal classification of user characteristics is described. The method comprises receiving audio and other inputs, extracting fundamental frequency information from the audio input, extracting other feature information from the video input, classifying the fundamental frequency information, textual information and video feature information using the multimodal neural network.
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公开(公告)号：US12277501B2
公开(公告)日：2025-04-15
申请号：US18217745
申请日：2023-07-03
Applicant: Sony Interactive Entertainment Inc.
Inventor： Sudha Krishnamurthy
Abstract: A Sound effect recommendation network is trained using a machine learning algorithm with a reference image, a positive audio embedding and a negative audio embedding as inputs to train a visual-to-audio correlation neural network to output a smaller distance between the positive audio embedding and the reference image than the negative audio embedding and the reference image. The visual-to-audio correlation neural network is trained to identify one or more visual elements in the reference image and map the one or more visual elements to one or more sound categories or subcategories within an audio database.
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公开(公告)号：US20240193865A1
公开(公告)日：2024-06-13
申请号：US18503079
申请日：2023-11-06
Applicant: Sony Interactive Entertainment Inc.
Inventor： Sudha Krishnamurthy , Michael Taylor
CPC classification number: G06T17/10 , G06N3/044 , G06T15/503 , G10L15/26 , G06T2210/21 , G06T2210/28
Abstract: A computer simulation object such as a chair is described by voice or photo input to render a 2D image. Machine learning may be used to convert voice input to the 2D image. The 2D image is converted to a 3D object and the 3D object or portions thereof are used in the computer simulation, such as a computer game, as the object such as a chair. A physics engine can be used to modify the 3D objects.
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公开(公告)号：US20230385646A1
公开(公告)日：2023-11-30
申请号：US18217745
申请日：2023-07-03
Applicant: Sony Interactive Entertainment Inc.
Inventor： Sudha Krishnamurthy
Abstract: A Sound effect recommendation network is trained using a machine learning algorithm with a reference image, a positive audio embedding and a negative audio embedding as inputs to train a visual-to-audio correlation neural network to output a smaller distance between the positive audio embedding and the reference image than the negative audio embedding and the reference image. The visual-to-audio correlation neural network is trained to identify one or more visual elements in the reference image and map the one or more visual elements to one or more sound categories or subcategories within an audio database.
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