Grammar Generation from Device Descriptors for Natural Language Interfaces
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Solution Overview
Problem
Developing natural language dialog systems is time-consuming and requires significant linguistic expertise, particularly in creating initial grammar rules, due to the need for expensive and difficult-to-obtain training corpora, and limited processing power and memory in mobile devices restrict grammar coverage.
Innovation Solution
A method and system that interactively create Natural Language User Interfaces (NL UI) by using a device descriptor to specify language interaction capabilities, automatically generating default grammar rules, and allowing developers to accept, revise, or augment these rules, ensuring adequate grammar coverage based on device capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional grammar creation methods are used requiring training corpora, then grammar accuracy can be improved, but the time and cost required increases significantly
Solution Approach 1:
The system performs preliminary actions by automatically generating initial grammar rules from device descriptors before developer intervention. The device descriptor contains pre-extracted information about device capabilities, interfaces, and domain objects that can be directly transformed into grammar rules, eliminating the need to start from scratch or require extensive training corpora.
Solution Approach 2:
The system creates grammar rules by copying and adapting templates based on device descriptor information. Instead of creating unique grammars for each device through time-consuming linguistic analysis, the system uses template grammar rules that can be instantiated with device-specific parameters from the descriptor, significantly reducing creation time while maintaining accuracy.
2Measurement precision
If comprehensive grammar coverage is provided, then speech recognition accuracy improves, but device memory and processing requirements increase
Solution Approach 1:
The system applies local quality by generating grammar rules that are specifically tailored to each device's capabilities as described in the device descriptor. Rather than using a single comprehensive grammar for all devices, the system creates localized grammars that include only the domain objects, interfaces, and parameters relevant to that specific device, reducing memory usage while maintaining recognition accuracy for device-specific commands.
Solution Approach 2:
The system changes parameters by dynamically adjusting grammar coverage based on device capabilities. The device descriptor provides information about available memory, processing power, and supported features, which the system uses to parameterize the grammar generation process. This allows the grammar size and complexity to be adapted to match the device's resource constraints while still providing adequate coverage for speech recognition.
3Adaptability or versatility
If developers manually create grammar rules from scratch, then grammar can be customized, but the complexity and expertise required increases
Solution Approach 1:
The system enables self-service by automatically generating grammar rules from device descriptors without requiring developers to manually create rules from scratch. The device descriptor contains all necessary information about device capabilities, and the system automatically transforms this information into customized grammar rules, reducing the complexity and expertise required while maintaining full customization capability.
Solution Approach 2:
The device descriptor acts as an intermediary between the device hardware and the grammar generation process. It provides a standardized interface that automatically extracts device capabilities and translates them into grammar rules, eliminating the need for developers to directly analyze device specifications and reducing the complexity of grammar creation while preserving customization.
Data Source
AI summary
A method, system, and tool product for creating a grammar for a natural language dialog system from a device description is provided. The system can include a device descriptor for identifying configuration, interface, object, and attribute information of the device, a speech grammar for identifying one or more rules generated from the device descriptor that are supported by the device, a speech recognition system for invoking rules of the speech grammar, and a processor for facilitating interoperability and development of distributed applications and providing delineated coverage of the one or more rules in view of the device descriptor.