Real-Time Dialogue Response Generation Using Intent Polarity Analysis
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Solution Overview
Problem
Existing dialogue response systems struggle to handle complex utterances effectively, leading to inefficiencies in conversation time and response relevance, as they fail to accurately identify intents and generate appropriate responses in real-time.
Innovation Solution
A method and system that analyze user utterances to identify labels, determine intents based on context, and generate responses by assessing polarity on a predefined scale, allowing for real-time generation of relevant and concise responses, including clarification questions when necessary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing dialogue response systems process complex utterances using traditional methods, then they can maintain system simplicity, but they fail to accurately identify intents and generate relevant responses, leading to increased conversation time and reduced productivity
Solution Approach 1:
The system segments complex utterances into multiple dialog acts by identifying different intents within a single user input. Each dialog act is processed independently with its own polarity determination, allowing the system to handle multiple concerns in one response and reduce the number of interaction turns needed.
Solution Approach 2:
The system introduces a polarity dimension (positive/negative/neutral scale) to intent analysis, enabling more nuanced understanding of user sentiment and intent strength. This additional dimension allows the system to generate more accurate responses by considering not just what the user wants but also their attitude toward it.
2Productivity
If existing systems use simplified processing for user utterances, then they can maintain fast response generation, but they fail to handle complex sentences with multiple dialog acts, reducing response relevance
Solution Approach 1:
The system divides complex utterances into separate dialog acts for individual processing. Each dialog act is analyzed for its specific intent and polarity, then responses are generated for each segment. This segmentation allows the system to maintain efficiency while accurately handling complex multi-intent utterances.
Solution Approach 2:
The system changes the processing parameters by introducing polarity values (positive, negative, neutral) and confidence scores for each identified intent. This parameter-based approach enables the system to prioritize and weight different intents appropriately, improving response relevance while maintaining processing efficiency.
3Measurement precision
If the system performs comprehensive intent analysis with polarity determination, then it can improve response accuracy and relevance, but it increases processing complexity and computational requirements
Solution Approach 1:
The system segments the complex task of utterance analysis into distinct steps: dialog act identification, intent extraction, polarity determination, and response generation. Each step handles a specific aspect of the analysis, reducing the complexity of any single processing component while achieving comprehensive analysis through the combination of segments.
4Reliability
If the system generates multiple responses for complex utterances, then it can improve response sufficiency and drive intent-specific conversation, but it increases the complexity of response management
Solution Approach 1:
The system generates one response per identified dialog act rather than attempting to generate a single comprehensive response. This segmentation of response generation simplifies the management complexity while ensuring that each aspect of the user's complex utterance receives adequate attention in a dedicated response.
Data Source
AI summary
The present disclosure discloses method and response generation system for generating dialogue responses for users in real-time. The response generation system receives pair of utterance from one or more sources, where pair of utterance comprise conversation between user and computing device, identifies one or more labels from utterance of pair of utterance that corresponds to user, where one or more labels exhibit relationship. One or more intent corresponding to each of identified one or more labels is determined, where one or more intent is restricted according to current context of utterance of user. A polarity of each of one or more intent is determined based on pre-defined scale comprising left bound and right bound and one or more responses for user are generated until determined polarity for each of labels from identified one or more labels is within pre-defined distance of left bound or right bound of pre-defined scale.