18339670. SCENE-AWARE SPEECH RECOGNITION USING VISION-LANGUAGE MODELS simplified abstract (NVIDIA Corporation)
Contents
- 1 SCENE-AWARE SPEECH RECOGNITION USING VISION-LANGUAGE MODELS
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 SCENE-AWARE SPEECH RECOGNITION USING VISION-LANGUAGE MODELS - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
SCENE-AWARE SPEECH RECOGNITION USING VISION-LANGUAGE MODELS
Organization Name
Inventor(s)
Gal Chechik of Ramat Hasharon (IL)
SCENE-AWARE SPEECH RECOGNITION USING VISION-LANGUAGE MODELS - A simplified explanation of the abstract
This abstract first appeared for US patent application 18339670 titled 'SCENE-AWARE SPEECH RECOGNITION USING VISION-LANGUAGE MODELS
Simplified Explanation
The patent application describes a system that generates a latent space model of a scene or video and applies this model, along with candidate sentences formed from digital audio, to a vision-language matching model to improve speech-to-text conversion accuracy.
- Latent space model generation:
- Scene or video is analyzed to create a latent space where similar features are closer to each other. - Digital audio is also analyzed to generate an embedding.
- Vision-language matching model utilization:
- The latent space embedding of the scene and digital audio is used to enhance transcription accuracy. - The model improves the interpretation of the digital audio embedding.
Potential Applications
The technology can be applied in: - Speech recognition systems - Video content analysis - Language translation services
Problems Solved
The technology addresses issues such as: - Inaccurate speech-to-text conversion - Difficulty in matching audio with visual content
Benefits
The system offers benefits like: - Improved accuracy in transcribing audio - Enhanced understanding of visual scenes - Efficient language processing
Potential Commercial Applications
The technology can be utilized in: - Virtual assistants - Video editing software - Language learning platforms
Possible Prior Art
There may be prior art related to: - Latent space modeling in audio-visual analysis - Vision-language matching for transcription purposes
Unanswered Questions
How does the system handle complex scenes with multiple audio sources?
The system's ability to separate and analyze different audio sources within a complex scene is not explicitly mentioned in the abstract. This could be a potential limitation of the technology.
What is the computational complexity of generating and utilizing the latent space model?
The abstract does not provide information on the computational resources required for generating and utilizing the latent space model. Understanding the computational complexity is crucial for assessing the practicality of implementing this technology.
Original Abstract Submitted
A system to generate a latent space model of a scene or video and apply this latent space and candidate sentences formed from digital audio to a vision-language matching model to enhance the accuracy of speech-to-text conversion. A latent space embedding of the scene is generated in which similar features are represented in the space closer to one another. An embedding for the digital audio is also generated. The vision-language matching model utilizes the latent space embedding to enhance the accuracy of transcribing/interpreting the embedding of the digital audio.
