Simple affirmative response operating system for hands-free content navigation
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Solution Overview
Problem
Existing natural language voice recognition systems for mobile devices are limited in their ability to provide sustained interaction, rely on predefined command vocabularies, and struggle with dynamic content navigation, making them unsuitable for complex applications and requiring users to remember specific commands or keywords, which increases user burden and decreases accuracy.
Innovation Solution
A simple affirmative response operating system that allows users to interact with devices in a screen-free manner using a minimal number of commands, enabling sustained interaction by presenting lists of audio or visual items with optional response prompts and conclusions, allowing users to select and navigate content using voice input without relying on predefined commands.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If command-driven ASR systems use a limited vocabulary list for embedded systems, then the system can operate without a remote server and have simpler architecture, but the user burden increases as they must remember specific commands or keywords
Solution Approach 1:
The system automatically generates and updates the vocabulary list based on the application's data structures and content, eliminating the need for manual configuration and reducing user burden. The system serves itself by dynamically adapting to the application's requirements without external intervention.
Solution Approach 2:
The vocabulary list transitions from a static, predefined set of commands to a dynamic structure that automatically updates based on the application's data. The system continuously adapts the vocabulary to match the current context and available content, making it both comprehensive and easy to use.
2Adaptability or versatility
If command-driven ASR systems use a large vocabulary for complex applications, then the system can handle more complex tasks, but the accuracy of speech recognition decreases in embedded systems due to limited computational resources
Solution Approach 1:
The system segments the vocabulary generation process into distinct phases: data structure analysis, content extraction, and dynamic assembly. By breaking down the complex task of handling large vocabularies into manageable segments, the system maintains high speech recognition accuracy while supporting complex applications with diverse content types.
Solution Approach 2:
The system performs preliminary analysis of the application's data structures and content before generating the vocabulary list. This advance preparation allows the system to optimize the vocabulary for the specific application context, ensuring high recognition accuracy without requiring excessive computational resources during runtime.
3Loss of information
If the TTS output uses varied-length content with erratic pause delays, then the system can provide complete information, but the user experience deteriorates as users struggle to know when to speak and respond quickly enough
Solution Approach 1:
The system implements periodic pause intervals between TTS output segments, creating a rhythmic pattern that helps users anticipate when to respond. These regular pauses provide users with sufficient time to process information and formulate responses without creating awkward delays, improving interaction efficiency while maintaining information completeness.
Solution Approach 2:
The system incorporates feedback mechanisms that monitor user response timing and adjust TTS pause durations accordingly. By providing real-time feedback about user interaction patterns, the system optimizes the pace of information delivery to match user needs, ensuring complete information is conveyed while maintaining smooth interaction flow.
Data Source
AI summary
A simple affirmative response operating system is disclosed for selecting a data item from a list of options using a unique affirmative action. Text-based labels in a listing of content are converted to speech using an embedded text-to-speech engine and an audio output of a first converted label is provided. A listening state is entered into for a predefined pause time to await receipt of the simple affirmative action. If the simple affirmative action is performed during the predefined pause time, an associated content item is selected for output. If the simple affirmative action is not performed during the predefined pause time, an audio output of a next converted label in the list is provided. This protocol may be used to control a variety of computing devices safely and efficiently while a user is distracted or disabled from using traditional input methods.