Dynamic Gate Command Speech Grammar for Vehicle ASR
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Solution Overview
Problem
Modern automatic speech recognition (ASR) systems in vehicles often struggle to quickly and accurately interpret speech commands, leading to frustration among vehicle occupants due to their slow response and inability to recognize certain speech commands effectively.
Innovation Solution
The implementation of a method that involves receiving and analyzing speech commands, identifying gate commands associated with specific vehicle functions, storing these associations in a database, and modifying the speech grammar based on frequent command usage to enhance recognition accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional speech recognition methods are used without gate commands, then the system is simpler to implement, but the recognition accuracy and response speed are slower
Solution Approach 1:
The speech command is segmented into two parts: a gate command (e.g., 'find', 'go to', 'play') and a specific parameter (e.g., location, song title). The gate command acts as a classifier that narrows down the recognition scope, improving accuracy while maintaining manageable system complexity through structured segmentation.
Solution Approach 2:
The gate command is processed first to pre-classify the intent before the system processes the specific command parameters. This preliminary action filters the recognition space, allowing the system to focus computational resources on the relevant domain, thereby improving both accuracy and effective processing speed.
2Adaptability or versatility
If the ASR system uses a fixed speech grammar, then the system is easier to maintain, but it cannot adapt to different speech patterns and command variations
Solution Approach 1:
The speech grammar is made dynamic by organizing it hierarchically around gate commands. Each gate command has its own associated grammar rules and parameter expectations. This allows the system to adapt to different speech patterns by activating the appropriate grammar subset based on the detected gate command, providing versatility without requiring management of a single complex monolithic grammar.
Solution Approach 2:
The system changes grammatical parameters (such as expected word patterns, parameter types, and validation rules) based on the detected gate command. For example, the gate command 'find' triggers a grammar expecting location parameters, while 'play' triggers a grammar expecting media parameters. This parameter adaptation enables flexibility while keeping the underlying grammar structure manageable through contextual specialization.
3Speed
If the system processes every speech command with full analysis, then recognition accuracy is maximized, but the response time increases and user frustration grows
Solution Approach 1:
The gate command provides preliminary classification that narrows down the interpretation space before full command processing begins. This preliminary action allows the system to activate only the relevant processing pathways and parameter validation rules, significantly reducing computation time while maintaining accuracy through focused analysis of the specific command domain.
Solution Approach 2:
The command processing is segmented into stages: first identifying the gate command for quick classification, then processing the specific parameters based on the gate command type. This segmentation allows the system to provide early feedback on command recognition and process only the necessary portions of the command in detail, improving response speed without sacrificing overall interpretation accuracy.
Data Source
AI summary
A system and method of controlling an automatic speech recognition (ASR) system includes: receiving speech at the ASR system from a vehicle occupant that includes a command to control a vehicle function; identifying a gate command from the speech; associating the identified gate command with the command to control the vehicle function; storing the associated gate command and vehicle command in a database; receiving additional speech at the ASR system from the vehicle occupant; detecting the gate command in the additional speech; and accessing the stored gate command and vehicle command from the database.