Voice Engine Locale Settings Dynamic Adaptation
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Solution Overview
Problem
Mobile devices face challenges in voice recognition when handling incoming calls from users with different geographical locales, as the voice engine struggles to discern responses due to language and dialect differences, leading to inaccurate call handling.
Innovation Solution
Dynamically loading the voice engine locale settings of the called device with the caller's preferences, using caller-specific grammar files and language models to improve voice recognition and query generation, allowing for tailored communication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the voice engine uses the called device's locale settings for voice recognition, then the callee's language preferences are maintained, but the caller's responses cannot be accurately recognized when they speak in a different dialect or language
Solution Approach 1:
The voice engine's locale settings are made dynamic rather than static. The system automatically detects the caller's locale from incoming call data and switches the voice engine to use the appropriate locale settings during the call. This allows the voice recognition system to adapt its language and dialect parameters in real-time based on the communication context, resolving the contradiction between maintaining callee preferences and accommodating caller diversity.
Solution Approach 2:
The system changes the locale parameter of the voice engine based on the caller's characteristics. By extracting locale information from the incoming call (such as from caller ID or metadata) and dynamically adjusting the voice engine's locale setting, the system optimizes voice recognition accuracy for the specific caller while maintaining the ability to switch back to the callee's preferred locale after the call.
2Ease of operation
If the voice engine generates query messages using the called device's locale settings, then the callee's language is used, but the caller may not understand the query due to dialect or language differences
Solution Approach 1:
The query generation process dynamically adapts to the caller's locale. The system detects the caller's language preferences and configures the voice engine to generate query messages in the caller's preferred language or dialect. This ensures that callers can understand the queries presented to them during automated call handling, improving ease of operation while preventing loss of information through language barriers.
3Adaptability or versatility
If the voice engine is configured with multiple locale settings for different callers, then language compatibility improves, but the complexity of managing and switching locale settings increases
Solution Approach 1:
The system implements self-service locale detection and configuration. Rather than requiring manual setup of multiple locale settings, the voice engine automatically detects the caller's locale from incoming call data and configures itself accordingly. This self-service approach enables multi-language support while minimizing the complexity of locale management, as the system handles the detection and switching processes automatically without user intervention.
Solution Approach 2:
The system uses an intermediary mechanism to manage locale settings. A locale detection module acts as an intermediary between the incoming call data and the voice engine configuration, automatically extracting locale information and translating it into the appropriate voice engine settings. This intermediary layer simplifies the overall system architecture by centralizing the locale management logic and automating the switching process.
Data Source
AI summary
A method includes receiving an incoming call from a caller's device in a called device. A locale preference associated with the caller's device is determined. A voice engine in the called device is configured using locale settings associated with the determined locale preference. A query message is sent to the caller's device. A response to the query message is parsed using the voice engine. The incoming call is processed in the called device based on the response.