Samsung electronics co., ltd. (20240119238). SYSTEMS AND METHODS FOR DETERMINING SEMANTIC POINTS IN HUMAN-TO-HUMAN CONVERSATIONS simplified abstract

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SYSTEMS AND METHODS FOR DETERMINING SEMANTIC POINTS IN HUMAN-TO-HUMAN CONVERSATIONS

Organization Name

samsung electronics co., ltd.

Inventor(s)

Ranjan Kumar Samal of Odisha (IN)

Vivek Paul Joseph of Kozhikode (IN)

Raghavendra Hanumatasetty Ramasetty of Bangalore (IN)

SYSTEMS AND METHODS FOR DETERMINING SEMANTIC POINTS IN HUMAN-TO-HUMAN CONVERSATIONS - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240119238 titled 'SYSTEMS AND METHODS FOR DETERMINING SEMANTIC POINTS IN HUMAN-TO-HUMAN CONVERSATIONS

Simplified Explanation

The patent application describes a system and method for determining semantic points in a human-to-human conversation by analyzing natural language attributes of dialogue turns.

  • Identifying a human-to-human conversation with multiple dialogue turns
  • Analyzing natural language attributes of each dialogue turn
  • Deriving a transient state based on the natural language attributes
  • Deriving conversation nuances based on the natural language attributes
  • Dynamically storing information associated with the conversation, transient state, and conversation nuances
  • Determining semantic relations and dialogue timelines within the conversation based on the stored information
  • Generating semantic points corresponding to the determined semantic relations and dialogue timelines

Potential Applications

This technology could be applied in customer service interactions, language learning platforms, and speech analysis tools.

Problems Solved

This technology helps in understanding the context and nuances of human conversations, enabling better communication analysis and interpretation.

Benefits

The system provides a structured way to analyze and extract meaningful insights from human-to-human conversations, improving communication understanding and decision-making.

Potential Commercial Applications

Potential commercial applications include chatbot development, customer feedback analysis tools, and market research platforms.

Possible Prior Art

One possible prior art could be sentiment analysis tools used in social media monitoring to understand the tone and emotions expressed in online conversations.

Unanswered Questions

1. How does the system handle different languages and dialects in human-to-human conversations? 2. What are the privacy implications of storing and analyzing information from conversations?


Original Abstract Submitted

a system and a method for determining semantic points in a human-to-human conversation is provided. the method includes identifying the human-to-human conversation including a plurality of dialogue turns and determining natural language (nl) attributes form each dialogue turn. further, the method includes deriving a transient state, based on the one or more nl attributes. further, the method includes deriving one or more conversation nuances associated with the human-to-human conversation based on the one or more nl attributes. moreover, the method includes dynamically storing information associated with the human-to-human conversation based on the one or more nl attributes, the transient state, and the one or more conversation nuances associated with each dialogue turn and determining one or more semantic relations and associated dialogue timelines within the human-to-human conversation based on the dynamically stored information. additionally, the method includes generating semantic points corresponding to the determined one or more semantic relations and the associated dialogue timelines within the human-to-human conversation.

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