Topic-Based Virtual Assistant Interaction Without Wake Terms
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Solution Overview
Problem
Existing NLUI applications rely on express wake terms for initiating responses, leading to unnatural verbal interactions as they mimic human conversations poorly due to the need for repeated activation phrases.
Innovation Solution
An NLUI application determines a topic for an audio input without express wake terms by parsing and matching descriptive terms with pre-defined topics, using contextual cues to generate responses only when the input aligns with these topics, and adjusting response generation based on topic scores and user feedback.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If wake terms are used to activate NLUI application responses, then response activation reliability is improved, but verbal interaction naturalness deteriorates
Solution Approach 1:
The system performs preliminary topic classification and scoring before response generation. By pre-determining topics and their associated descriptive terms, the system can quickly match audio inputs to appropriate responses without requiring wake terms, thus maintaining reliability while improving naturalness.
Solution Approach 2:
The patent introduces topic-based intermediary classification as a mediator between audio input and response generation. Instead of directly responding to wake terms, the system uses topic matching as an intermediate step that enables context-aware responses without requiring explicit activation phrases.
2Ease of operation
If topic-based response generation is implemented, then verbal interaction naturalness is improved, but response generation complexity increases
Solution Approach 1:
The system segments the response generation process into distinct components: audio input parsing, topic determination, topic scoring, and response generation. This segmentation allows each component to be optimized independently, reducing overall complexity while maintaining natural interaction.
Solution Approach 2:
The patent changes the parameter for response activation from wake term detection to topic score thresholding. By using topic scores that can be adjusted based on user preferences and context, the system achieves flexible response generation without complex rule-based systems.
3Measurement precision
If multiple descriptive terms are used for topic determination, then topic classification accuracy is improved, but audio processing time increases
Solution Approach 1:
The system uses partial action by determining topic scores based on a subset of descriptive terms rather than all possible terms. This allows the system to achieve sufficient accuracy for topic classification without processing every possible term, thus reducing time consumption.
Solution Approach 2:
The patent implements feedback mechanisms where topic scores are adjusted based on user preferences and previous interactions. This feedback allows the system to refine topic classification over time, improving accuracy without requiring exhaustive processing of all descriptive terms for each input.
Data Source
AI summary
Systems and methods are disclosed for enabling verbal interaction with an NLUI application without relying on express wake terms. The NLUI application receives an audio input comprising a plurality of terms. In response to determining that none of the terms is an express wake term pre-programmed into the NLUI application, the NLUI application determines a topic for the plurality of terms. The NLUI application then determines whether the topic is within a plurality of topics for which a response should be generated. If the determined topic of the audio input is within the plurality of topics, the NLUI application generates a response to the audio input.