Paralinguistic Audio Analysis for Adaptive User Interface Personalization
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Solution Overview
Problem
Complex software applications struggle to provide personalized user experiences and content relevance due to the limitations of traditional interaction methods, which do not effectively utilize paralinguistic information to adapt user interfaces and content rankings.
Innovation Solution
A computer-implemented method and system that analyzes audio streams for paralinguistic information to determine user attributes, allowing for the selection of appropriate user interfaces, content, and actions, and adjusts content rankings based on user feedback and attributes, using techniques such as speech recognition and emotional analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional interaction methods are used to collect user feedback, then the system complexity remains low, but the ability to provide personalized user experiences and content relevance deteriorates
Solution Approach 1:
The system performs preliminary analysis of audio streams to extract paralinguistic information and determine user attributes before the user actually interacts with the content. This advance preparation enables personalized content selection and interface adaptation without adding complexity during the actual user interaction moment.
Solution Approach 2:
The patent introduces an intermediary processing layer that analyzes audio streams and extracts paralinguistic information. This intermediary component translates raw audio data into meaningful user attributes that can then be used for personalization, effectively bridging the gap between simple data collection and complex personalization requirements.
2Measurement precision
If paralinguistic information analysis is implemented, then user attribute determination accuracy improves, but processing time and computational resources increase
Solution Approach 1:
The system extracts only the essential paralinguistic information from audio streams that is directly relevant to determining user attributes. By selectively extracting only the necessary features rather than analyzing the complete audio signal, the system achieves accurate user attribute determination while minimizing processing time and computational overhead.
3Loss of information
If content rankings are adjusted based on user feedback and attributes, then content relevance improves, but the complexity of the recommendation system increases
Solution Approach 1:
The system applies different ranking strategies and weighting factors to different types of content based on user attributes. Rather than using a single complex ranking algorithm for all content, the system tailors the ranking approach locally to each content type and user attribute combination, achieving high content relevance while keeping the overall system manageable through modular, specialized ranking components.
Data Source
AI summary
Techniques are disclosed for adjusting user experience of a software application based on paralinguistic information. One embodiment presented herein includes a computer-implemented method for adjusting a user experience of a software application. The method comprises receiving, at a computing device, an audio stream comprising audio of a user. The method further comprises analyzing the audio stream for paralinguistic information to determine an attribute of the user. The method further comprises identifying content of the audio stream. The method further comprises determining one or more actions based on the content of the audio stream. The method further comprises selecting at least one of the one or more actions based on the attribute of the user.