Vehicle Dialogue System Speaker Priority Control
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Solution Overview
Problem
Current audio-video-navigation (AVN) devices in vehicles pose a safety risk during driving due to their small screens and buttons, requiring users to take their hands off the wheel or look away, making it inconvenient and dangerous to interact with them.
Innovation Solution
A dialogue system that recognizes user intentions through speech and provides services by selecting a leader among multiple speakers based on acquired speech patterns, relationships, and context information, allowing for voice-controlled vehicle functions without the need for manual input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a dialogue system is applied to recognize user intention through speech, then user safety is improved by allowing hands-on-wheel operation, but the system complexity increases due to speech recognition and speaker classification requirements
Solution Approach 1:
The dialogue system segments the speech recognition task by classifying speech into different speaker categories (driver, front passenger, rear passenger) based on acoustic characteristics. This segmentation allows the system to handle multiple speakers simultaneously and determine speaker priority, resolving the contradiction by organizing complexity into manageable segments while maintaining safety through accurate speaker identification
Solution Approach 2:
The system introduces a speaker classification module as an intermediary between speech input and intention recognition. This intermediary analyzes acoustic features to identify speaker categories and determines speaker priority, acting as a mediator that translates raw speech signals into structured speaker information that can be processed by the dialogue manager, thereby managing system complexity while improving safety
2Measurement precision
If speaker classification and relationship analysis are implemented, then service accuracy is improved by understanding user context, but processing time increases due to additional analysis steps
Solution Approach 1:
The system performs preliminary speaker classification and relationship establishment before main dialogue processing. By pre-analyzing acoustic characteristics to categorize speakers and pre-determining speaker relationships (driver, passenger, etc.), the system prepares structured speaker information in advance, reducing processing time during actual dialogue while maintaining high service accuracy through context-aware speaker prioritization
Solution Approach 2:
The system changes parameters by extracting specific acoustic features (pitch, timbre, spatial position) to classify speakers into categories. By transforming raw speech parameters into meaningful speaker attributes and relationship indicators, the system achieves accurate speaker identification and context understanding efficiently, balancing processing time with service accuracy
3Adaptability or versatility
If multiple speakers are supported with priority determination, then adaptability is improved by handling various dialogue scenarios, but device complexity increases due to priority determination mechanisms
Solution Approach 1:
The system applies local quality by assigning different priority levels to different speaker positions (driver highest, front passenger medium, rear passenger lowest). This localized quality assignment based on speaker location and role allows the system to handle multiple dialogue scenarios adaptively while managing complexity through a simple priority hierarchy rather than complex decision-making mechanisms
Data Source
AI summary
A dialogue system, a vehicle and a method for controlling the vehicle is disclosed. The method for controlling the vehicle includes: acquiring an utterance and a speech pattern by recognizing a speech when a speech of a plurality of speakers is input through a speech input device; classifying dialogue contents for each speaker based on the acquired utterance and speech pattern; acquiring a relationship between the speakers based on the acquired utterance; understanding an intention and a context for each speaker based on the acquired relationship between the speakers and the acquired dialogue content for each speaker determining an action corresponding to the acquired relationship and the acquired intention and context for each speaker, and outputting an utterance corresponding to the determined action; generating a control command corresponding to the determined action; and controlling a load based on the generated control command.