Patent Applications published on Jun 5, 2025

Explore the 9,078 U.S. Patent Applications published on the 23rd week of 2025, including 1,676 applications that subsequently received a Patent Grant.

Featured patent applications from Jun 5, 2025

Published: 2025-06-05
US20250182401A1
Physics
Application 20250182401, fig. 01

SYSTEMS AND METHODS FOR CAPTURING, TRANSPORTING, AND REPRODUCING THREE-DIMENSIONAL SIMULATIONS AS INTERACTIVE VOLUMETRIC DISPLAYS

A new technology allows users to capture and transport 3D simulations for display. It can show these simulations in real-time or from recordings. Multiple users can interact with the 3D visuals together. The system works with simulations created by other applications. This makes it easier for people to experience virtual and mixed reality environments collaboratively.

Published: 2025-06-05 Assignee: Science Corporation.
US20250181903A1
Physics
Application 20250181903, fig. 01

NEURAL INTERFACE DEVICE

A neural interface device connects the brain to a computer or other devices. It has a controller, scaffolds, and a tissue interface to help it work properly. This device can be placed directly on the surface of the brain. It can also work with external devices for additional functions. Overall, it aims to improve communication between the brain and technology.

Published: 2025-06-05 Assignee: TOYOTA JIDOSHA KABUSHIKI KAISHA, TOYOTA JIDOSHA KABUSHIKI KAISHA, Toyota Research Institute, Inc..
US20250181612A1
Physics
Application 20250181612, fig. 01

SYSTEM AND METHOD FOR LEARNING AND COMMUNICATING IMPLICIT STYLISTIC PREFERENCES FROM HISTORICAL USER INTERACTION DATA IN TEXT-TO-IMAGE PROMPT ENGINEERING

A new system helps create images based on user preferences by analyzing past interactions. It generates multiple images for each prompt given by a user and connects these images to show relationships between them. Another user can then choose their favorite set of images from the options provided. The system displays these choices in a visual format, making it easy to see preferences. This approach enhances how users interact with image generation tools by personalizing the results.

Published: 2025-06-05 Assignee: Sony Interactive Entertainment Inc..
US20250177871A1
Human necessities
Application 20250177871, fig. 01

SYSTEMS AND METHODS FOR DYNAMIC CHAT TRANSLATION

A new system helps translate chat messages in real-time during electronic games. It takes messages from players and changes parts of them into a language that the player understands using advanced technology. This makes it easier for players to understand what is being said in the game, including messages from characters that are not controlled by players. The system can also track how players react, like where they look, to improve the translation process. Overall, it aims to enhance communication and enjoyment in gaming experiences.

Published: 2025-06-05 Assignee: SIEMENS AKTIENGESELLSCHAFT.
US20250182737A1
Physics

Speech Synthesizer and Method for Speech Synthesis

A speech synthesizer uses a computer to understand and create human-like speech. It has a special part that analyzes language and another part that adds emotions to the spoken words. A microphone captures sound, while memory stores recordings of real and artificial speech. The system uses a neural network to help decide how to express emotions in the speech. It learns from examples provided by humans to improve its ability to sound natural and emotional.

Published: 2025-06-05 Assignee: IQSpark LLC.
US20250181312A1
Physics
Application 20250181312, fig. 01

AI-Based Audio Digest System and Related Methods

An AI-based audio digest system creates personalized audio content by using data from different sources. It organizes various audio clips into a sequence that matches what a user likes and needs. Users can interact with the audio through voice commands or touch controls. The system adjusts the details of the audio based on the user's situation and offers privacy settings for security. Additionally, it provides updates and insights, supports multiple languages, and allows interaction with visual elements using augmented reality.

Published: 2025-06-05
US20250182524A1
Physics
Application 20250182524, fig. 01

FACIAL SYNTHESIS IN AUGMENTED REALITY CONTENT FOR ONLINE COMMUNITIES

A computing device captures images of a person's face and their facial expressions, including how they move their lips. It then uses these images along with other media to create specific pose settings. Users can choose a particular facial expression from a list of options. Based on this choice and the pose settings, new media content is generated. Finally, this content is displayed as augmented reality for users to see on their devices.

Published: 2025-06-05 Assignee: Magic Leap, Inc..
US20250182413A1
Physics
Application 20250182413, fig. 01

SYSTEMS AND METHODS FOR AUGMENTED REALITY

An augmented reality viewer helps users see and experience a mix of the real world and digital images. It uses special parts and software to create these experiences. Users can interact with virtual elements that look like they are part of their real surroundings. The technology can show exciting features, including those from underwater environments. Overall, it makes exploring and learning about different worlds more engaging and fun.

Published: 2025-06-05
US20250182607A1
Physics
Application 20250182607, fig. 01

PERSONAL PROTECTIVE EQUIPMENT COMPLIANCE AND PERSONAL WELLNESS MONITORING SYSTEM WITH INTELLIGENT CONNECTED FACESHIELDS

A new system uses smart headgear and faceshields to keep people safe and healthy. These wearable items have sensors that can talk to each other. They check if everyone is following safety rules and also monitor personal health. This technology helps ensure that people in a community are protected and well. It combines personal safety gear with wellness tracking for better overall safety.

Published: 2025-06-05
US20250182420A1
Physics
Application 20250182420, fig. 01

PIXEL DEPTH DETERMINATION FOR OBJECT

The process involves using images of people to add augmented reality (AR) features. First, an image is received that shows a person. Then, a machine learning model predicts how far away certain points are within that image. Another model helps determine the depth of each pixel in relation to those points. Finally, AR elements are added to the image based on this depth information.