Offline Embedded Natural Language Interface
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Solution Overview
Problem
Existing natural language processing systems struggle to implement effective speech and language understanding in offline embedded systems, particularly due to the limitations of formal semantics and the inability to handle incomplete or imperfect information, making it difficult to scale beyond simple commands and operate without an internet connection.
Innovation Solution
A compositional and precise speech and natural language understanding system is developed, utilizing a grammar-grounded projection algorithm for improved speech recognition and a compositional language interface with interactive semantic evaluation, which restricts vocabulary and grammar to a well-defined subset of a natural language, allowing for precise communication and handling incomplete information through a phonetic distance-based approach.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a full natural language processing system is implemented, then the system can handle incomplete or imperfect information and scale beyond simple commands, but the device complexity and computational resources required become too high for offline embedded systems
Solution Approach 1:
The patent segments the natural language processing system into distinct modular components: automatic speech recognition (ASR) module, grammar projection module, and interpreter module. Each module handles a specific aspect of processing, allowing the system to manage complexity through division while maintaining offline embedded system capabilities.
Solution Approach 2:
The grammar projection module serves as an intermediary between the ASR and interpreter modules. It projects grammars from the application programming interface (API) to the ASR module, enabling the system to handle incomplete or imperfect information by providing structural guidance without requiring full natural language processing capabilities.
2Measurement precision
If cloud-based speech recognition and processing systems are used, then the system can achieve high accuracy, but the system cannot operate without an internet connection
Solution Approach 1:
The embedded natural language processing system is designed to perform multiple functions locally without requiring cloud connectivity. It combines speech recognition, grammar projection, and semantic interpretation capabilities in a single offline system, enabling universal operation across different environments with or without internet access.
3Speed
If the vocabulary and grammar are restricted to a well-defined subset, then the system can operate offline with low latency, but the system's ability to understand diverse natural language inputs is limited
Solution Approach 1:
The grammar projection module dynamically adapts grammars based on the specific application and context. Rather than using a static restricted vocabulary, the system projects grammars from the API to match the specific domain requirements, enabling flexible language understanding while maintaining fast offline processing through targeted grammar generation.
Data Source
AI summary
It is not trivial to implement speech and natural language processing in offline embedded systems. Voice control of devices in various settings and applications can benefit from an embedded speech and natural language processing solution. One feature that helps to correct automatic speech recognition outputs is grammar projection. Another feature addresses situations where there is imperfect information or incomplete information by providing an application programming interface to enable structured queries and responses between an interpreter and an application.