18126212. SYSTEMS AND METHODS FOR RECONSTRUCTING VIDEO DATA USING CONTEXTUALLY-AWARE MULTI-MODAL GENERATION DURING SIGNAL LOSS simplified abstract (Verizon Patent and Licensing Inc.)
SYSTEMS AND METHODS FOR RECONSTRUCTING VIDEO DATA USING CONTEXTUALLY-AWARE MULTI-MODAL GENERATION DURING SIGNAL LOSS
Organization Name
Verizon Patent and Licensing Inc.
Inventor(s)
Saurabh Tahiliani of Noida (IN)
SYSTEMS AND METHODS FOR RECONSTRUCTING VIDEO DATA USING CONTEXTUALLY-AWARE MULTI-MODAL GENERATION DURING SIGNAL LOSS - A simplified explanation of the abstract
This abstract first appeared for US patent application 18126212 titled 'SYSTEMS AND METHODS FOR RECONSTRUCTING VIDEO DATA USING CONTEXTUALLY-AWARE MULTI-MODAL GENERATION DURING SIGNAL LOSS
Simplified Explanation:
The patent application describes a device that can process video data, detect network fluctuations, generate a new phrase from a text transcript, create a response phoneme, and combine audio, image, and text embeddings to produce a final voice response and video output.
Key Features and Innovation:
- Device processes video data with text transcript, audio sequences, and image frames.
- Detects network fluctuations.
- Generates new phrase and response phoneme.
- Creates text, audio, and image embeddings.
- Combines embeddings to produce final voice response and video.
Potential Applications: This technology could be used in video conferencing, virtual assistants, language translation, and content creation applications.
Problems Solved: This technology addresses the need for more natural and personalized voice responses in video communication and content creation.
Benefits:
- Enhanced user experience with more natural voice responses.
- Improved content creation capabilities.
- Better adaptation to network fluctuations.
Commercial Applications: Potential commercial applications include video conferencing software, virtual assistant devices, and content creation tools for social media platforms.
Prior Art: Prior art related to this technology may include research on natural language processing, voice synthesis, and video processing algorithms.
Frequently Updated Research: Researchers are constantly exploring advancements in natural language processing, voice synthesis, and video processing techniques that could enhance the capabilities of this technology.
Questions about the Technology: 1. How does this technology improve user interactions in video communication? 2. What are the potential limitations of this technology in handling complex audio and visual data?
Original Abstract Submitted
A device may receive video data that includes a text transcript, audio sequences, and image frames, and may detect a network fluctuation. The device may process the text transcript to generate a new phrase, and may generate a response phoneme based on the new phrase. The device may generate a text embedding based on the response phoneme, and may process the audio sequences to generate a target voice sequence. The device may generate an audio embedding based on the target voice sequence, and may process the image frames to generate a target image sequence. The device may generate an image embedding based on the target image sequence, and may combine the embeddings to generate an embedding input vector. The device may generate a final voice response and a final video based on the embedding input vector, and may provide the video data, the final voice response, and the final video.
