Voice Recognition Circuitry for Automatic Language Detection
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Solution Overview
Problem
Conventional systems fail to seamlessly and automatically determine user preferences for content language, making it difficult for users to select appropriate content and for content providers to recommend relevant content.
Innovation Solution
The system uses voice recognition circuitry to determine the language spoken in a household by monitoring conversations and measuring the duration of spoken languages. It then cross-references a database of content sources to identify those associated with the determined language, generating a representation of these content sources for display to the user.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual language preference specification is used, then user control over content selection is improved, but system automation and ease of operation deteriorate
Solution Approach 1:
The system automatically detects the language spoken in the household through voice recognition circuitry without requiring manual user input. The media guidance application monitors conversations, determines the primary language, and uses this information to automatically filter and present content in that language, making the system self-configuring and eliminating manual preference specification.
Solution Approach 2:
The patent replaces manual mechanical interaction (users manually selecting language preferences) with an automated acoustic field-based system (voice recognition circuitry that listens to and analyzes household conversations to automatically determine language preferences).
2Extent of automation
If voice recognition circuitry is implemented, then automatic language determination is improved, but device complexity increases
Solution Approach 1:
The voice recognition circuitry and media guidance application serve multiple functions: they not only detect language preferences but also continuously monitor household conversations, automatically filter content based on detected languages, and dynamically update content recommendations. This multi-functionality justifies the added complexity by providing comprehensive automated content management.
3Loss of information
If content filtering by language is implemented, then content relevance is improved, but information loss occurs
Solution Approach 1:
The system dynamically adjusts content filtering based on the detected primary language of the household. Rather than static filtering, the media guidance application continuously monitors language usage patterns and adapts its content recommendations in real-time, presenting content that matches the currently detected primary language while maintaining the ability to switch if language patterns change.
Data Source
AI summary
Systems and methods for identifying content corresponding to a language are provided. Language spoken by a first user based on verbal input received from the first user is automatically determined with voice recognition circuitry. A database of content sources is cross-referenced to identify a content source associated with a language field value that corresponds to the determined language spoken by the first user. The language field in the database identifies the language that the associated content source transmits content to a plurality of users. A representation of the identified content source is generated for display to the first user.