Text-to-Speech System for Commute-Aware Audio Content Generation
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Solution Overview
Problem
Users face challenges in accessing and consuming information while commuting or traveling, as existing solutions do not efficiently convert data content into audible representations tailored to individual preferences and travel time.
Innovation Solution
A computer program product generates custom-length, custom-content audible representations based on user history and preferences, using text-to-speech technology to convert data content into speech that fits within the user's commute time, with adjustments for storage capacity and playback devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If text-to-speech conversion is applied to convert data content into audible representations, then information accessibility during travel is improved, but the content may not be tailored to individual user preferences or travel time constraints
Solution Approach 1:
The system performs preliminary actions by analyzing user browsing history and content preferences before generating the audible representation. It pre-selects relevant content and determines appropriate duration based on available travel time, ensuring the content is personalized and time-appropriate before the user begins their journey.
Solution Approach 2:
The system dynamically adapts the audible representation to match the user's specific travel time constraints. It adjusts the content selection and duration based on real-time parameters such as commute length and user preferences, making the solution flexible and tailored to individual circumstances rather than using a fixed approach.
2Loss of information
If comprehensive content is included in the audible representation, then information completeness is improved, but the duration may exceed available travel time
Solution Approach 1:
The system extracts and selects only the most relevant content from available data sources based on user browsing history and preferences. It filters out unnecessary information and focuses on delivering key insights that align with user interests, thereby maintaining information value while reducing overall duration to fit travel constraints.
Solution Approach 2:
The system applies partial action by providing a curated subset of content that is sufficient for the user's information needs during travel, rather than delivering all available content. It strikes a balance between completeness and conciseness, delivering enough information to be valuable while respecting time limitations.
3Adaptability or versatility
If custom-content audible representations are generated for each user, then content relevance is improved, but system complexity increases
Solution Approach 1:
The system implements self-service by automatically analyzing user browsing history, determining content preferences, and selecting appropriate content without requiring manual user input. It autonomously generates personalized audible representations by processing available data and making intelligent decisions about content selection and duration optimization.
Solution Approach 2:
The system uses feedback from user browsing history and interaction patterns to continuously improve content selection. It analyzes past behavior to understand user preferences and adjusts content recommendations accordingly, creating a refined feedback loop that enhances personalization while managing system complexity through data-driven decision-making.
Data Source
AI summary
A custom-content audible representation of selected data content is automatically created for a user. The content is based on content preferences of the user (e.g., one or more web browsing histories). The content is aggregated, converted using text-to-speech technology, and adapted to fit in a desired length selected for the personalized audible representation. The length of the audible representation may be custom for the user, and may be determined based on the amount of time the user is typically traveling.