Natural Language Dialogue System Intent Correction
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Solution Overview
Problem
Conventional natural language dialogue systems face challenges in accurately recognizing user intentions due to rigid input rules and the inability to handle diverse user inputs, leading to incorrect interpretations and inefficient search results, as they rely on predefined phrase lists and struggle with colloquial expressions and complex sentences.
Innovation Solution
A natural language dialogue system that includes a speech sampling module and a natural language comprehension system, capable of parsing keywords to generate candidate lists of report answers, allowing for the selection and correction of speech responses based on user feedback, thereby providing accurate and relevant information through a structured database search.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If predefined phrase lists are used to recognize user intentions, then recognition accuracy improves for standard expressions, but the system cannot handle diverse colloquial expressions and complex sentences
Solution Approach 1:
The system dynamically adjusts its processing approach based on input characteristics. For standard expressions matching predefined phrases, it uses direct matching for accuracy. For diverse colloquial expressions, it transitions to keyword extraction and structured database searching, allowing the system to adapt its recognition method to the specific input type.
Solution Approach 2:
The system changes the processing parameters based on the input type. When predefined phrase matching fails or the input is complex, it shifts from exact matching parameters to fuzzy keyword matching parameters, extracting key terms and searching structured databases with adjusted search criteria to handle the diversity of user expressions.
2Adaptability or versatility
If full-text search is used to handle diverse user inputs, then adaptability improves, but search results become non-structured and require time-consuming browsing
Solution Approach 1:
The system segments the search process into distinct stages: keyword extraction from user input, structured database searching based on extracted keywords, and organized result presentation. This segmentation allows the system to maintain adaptability while delivering structured, immediately usable results without requiring users to browse through unorganized full-text search outputs.
Solution Approach 2:
The system introduces an intermediary processing layer between user input and search results. This intermediary extracts keywords and uses them to query structured databases, acting as a mediator that transforms diverse user inputs into targeted, structured searches, thereby reducing the time users need to spend browsing results while maintaining high adaptability.
3Adaptability or versatility
If multiple possible interpretations are provided for ambiguous sentences, then recognition coverage improves, but user efficiency decreases due to redundant selections
Solution Approach 1:
The system uses feedback from user corrections to improve future recognitions. When users correct misinterpreted speech responses, the system learns from these corrections and adjusts its interpretation strategy, maintaining high recognition coverage while improving efficiency by reducing redundant options in future interactions based on accumulated feedback.
Solution Approach 2:
The system performs preliminary analysis of user input to identify the most likely interpretation before presenting options to users. By pre-processing the input and ranking possible interpretations based on probability and context, it reduces the number of redundant options users need to evaluate, thereby maintaining comprehensive coverage while improving interaction efficiency.
Data Source
AI summary
A natural language dialog system and a method capable of correcting a speech response are provided. The method includes following steps. A first speech input is received. At least one keyword included in the first speech input is parsed to obtain a candidate list having at least one report answers. One of the report answers is selected from the candidate list as a first report answer, and a first speech response is output according to the first report answer. A second speech input is received and parsed to determine whether the first report answer is correct. If the first report answer is incorrect, another report answer other than the first report answer is selected from the candidate list as a second report answer. According to the second report answer, a second speech response is output.