Layered Grammar Library for Speech Recognition
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current speech recognition systems face inefficiencies due to the complexity of grammar recognition network representations, such as the Hidden Markov Model Toolkit (HTK) Standard Lattice Format (SLF), which requires large memory and lacks integration with pronunciation dictionaries, leading to difficulties in error visibility and synchronization between grammar and dictionary components.
Innovation Solution
A method is introduced to optimize grammar structure by identifying and eliminating redundant nodes, grouping nodes, and fusing them to create an optimized grammar structure, which is then integrated into a unified layered grammar and dictionary library, allowing for efficient processing of voice input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If the Hidden Markov Model Toolkit (HTK) Standard Lattice Format (SLF) is used to represent grammar recognition network, then the grammar structure can be explicitly defined with nodes and links, but the memory usage increases and the structure becomes difficult to handle
Solution Approach 1:
The patent merges the grammar recognition network with the pronunciation dictionary into a unified structure. The dictionary is organized as a layered structure where the first layer contains grammar rules and the second layer contains phonetic transcriptions. This integration eliminates the need for separate node and link representations, reducing memory usage while maintaining explicit structure definition capabilities.
Solution Approach 2:
The patent segments the grammar and dictionary into distinct layers within a unified structure. The grammar portion is separated into rules and patterns, while the dictionary is organized into word entries with phonetic transcriptions. This segmentation allows for efficient memory management and easier handling of each component independently.
2Adaptability or versatility
If grammar recognition network and pronunciation dictionary are kept as separate entities, then each component can be independently managed, but error visibility and synchronization between components become difficult
Solution Approach 1:
The patent combines the grammar recognition network and pronunciation dictionary into a single integrated data structure. Errors in either component can be detected and corrected within the unified structure, improving error visibility. The integrated structure ensures that changes in grammar rules are automatically synchronized with the dictionary, maintaining consistency across both components.
Solution Approach 2:
The unified structure incorporates cross-references and validation mechanisms that provide feedback between what was previously separate components. When grammar rules are defined, the system automatically validates them against the dictionary entries, and vice versa, ensuring synchronization and immediate error detection.
3Device complexity
If SLF nodes represent only one word per node, then the structure is simple and explicit, but a large memory object is required to handle the grammar
Solution Approach 1:
The patent merges multiple words that share common phonetic transcriptions into single dictionary entries. Instead of creating separate nodes for each word occurrence, the unified structure stores the phonetic transcription once and references it from multiple grammar rules, significantly reducing memory usage while maintaining the ability to represent complex grammars.
Solution Approach 2:
The unified structure creates multi-functional representations where a single dictionary entry can serve multiple grammar rules. The phonetic transcription data structure is designed to be universally applicable across different word entries and grammar contexts, reducing redundancy and memory requirements.
Data Source
AI summary
A speech recognition engine is provided with an acoustic model and a layered grammar and dictionary library. The layered grammar and dictionary library includes a language and non-grammar layer that supplies types of rules a grammar definition layer can use and defines non-grammar the speech recognition engine should ignore. The layered grammar and dictionary library also includes a dictionary layer that defines phonetic transcriptions for word groups the speech recognition engine is meant to recognize when voice input is received. The layered grammar and dictionary library further includes a grammar definition layer that applies rules from the language and non-grammar layer to define combinations of word groups the speech recognition system is meant to recognize. Voice input is received at a speech recognition engine and is processed using the acoustic model and the layered grammar and dictionary library.