Amazon Technologies, Inc. (20240331686). RELEVANT CONTEXT DETERMINATION simplified abstract
Contents
RELEVANT CONTEXT DETERMINATION
Organization Name
Inventor(s)
Thanh Dac Tran of Logan UT (US)
Grant Strimel of Presto PA (US)
RELEVANT CONTEXT DETERMINATION - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240331686 titled 'RELEVANT CONTEXT DETERMINATION
The patent application describes techniques for determining and storing relevant context information for a user input, such as a spoken input. Context information is determined to be relevant on an audio frame basis, with context scores for different types of context data being calculated for individual audio frames. The most relevant context is then stored in a local context cache based on these scores, which is updated as subsequent audio frames are processed. The data stored in the context cache is provided to downstream components for tasks such as ASR, NLU, and SLU.
- Context information is determined to be relevant on an audio frame basis.
- Context scores for different types of context data are calculated for individual audio frames.
- The most relevant context is stored in a local context cache based on these scores.
- The local context cache is updated as subsequent audio frames are processed.
- The data stored in the context cache is provided to downstream components for tasks such as ASR, NLU, and SLU.
Potential Applications: - Speech recognition systems - Natural language understanding systems - Conversational AI applications
Problems Solved: - Efficient storage and retrieval of context information for user inputs - Improved accuracy in understanding user intent in spoken interactions
Benefits: - Enhanced user experience in voice-controlled devices - Increased accuracy in speech recognition and understanding - Streamlined processing of spoken inputs in AI systems
Commercial Applications: Title: Contextual Speech Recognition Technology for Enhanced User Interactions This technology can be utilized in: - Virtual assistants - Smart home devices - Customer service chatbots
Questions about Contextual Speech Recognition Technology: 1. How does this technology improve the accuracy of speech recognition systems? 2. What are the potential privacy concerns associated with storing user context information in a local cache?
Frequently Updated Research: Stay updated on advancements in speech recognition technology and AI systems for improved context understanding and user interactions.
Original Abstract Submitted
techniques for determining and storing relevant context information for a user input, such as a spoken input, are described. in some embodiments, context information is determined to be relevant on an audio frame basis. context scores for different types of context data (e.g., prior dialog turn data, user profile data, device information, etc.) are determined for individual audio frames corresponding to a spoken input. based on the corresponding context scores, the most relevant context is stored in a local context cache. the local context cache is updated as subsequent audio frames, of the user input, are processed. the data stored in the context cache is provided to downstream components to perform tasks such as asr, nlu and slu.
