In-Vehicle Speech Recognition with User Prompt Removal
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Solution Overview
Problem
Existing speech recognition technologies in vehicles are uncomfortable and inefficient, leading to reduced user interaction and poor recognition performance due to unspecific noise interference and user anxiety, which limits data collection and technological development.
Innovation Solution
An apparatus and method that includes a user prompt playback unit to play a personalized sound source, a microphone detection signal extraction unit to identify speech, a user prompt removal unit to eliminate noise, and a speech recognition unit to process the speech, enhancing user comfort and recognition accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional speech recognition is used in vehicles, then speech recognition function is provided, but user comfort and recognition accuracy deteriorate due to awkward speaking environment and lack of personalization
Solution Approach 1:
The speech recognition system is segmented into multiple functional modules: prompt generation module, speech detection module, speech recognition module, and response generation module. This segmentation allows each module to be optimized independently, improving both user comfort and recognition accuracy while maintaining ease of operation.
Solution Approach 2:
The system performs preliminary actions by generating and playing customized audio prompts before speech recognition begins. This preliminary customization of the speaking environment based on user preferences improves user comfort and reduces anxiety, which in turn enhances recognition accuracy by creating optimal conditions for speech input.
2Productivity
If speech recognition begins with traditional mute environment, then speech processing is simplified, but user anxiety increases and speaking time is reduced
Solution Approach 1:
The system introduces an intermediary audio prompt between the user and the speech recognition process. This intermediary element guides the user through the speech input process, reducing anxiety and encouraging more extensive speech input, thereby increasing both speaking time and the quantity of speech data collected for training.
Solution Approach 2:
The system implements feedback mechanisms where the audio prompt and response are customized based on user preferences and speech patterns. This feedback loop enhances user confidence and encourages longer, more natural speech input, improving productivity while minimizing information loss through better recognition of extended speech data.
3Reliability
If standardized speech recognition is deployed, then development cost is reduced, but recognition performance reaches threshold limit due to lack of user-specific optimization
Solution Approach 1:
The system changes key parameters of the speech recognition process based on user preferences, including audio prompt characteristics, sensitivity thresholds, and response formatting. These parameter adjustments improve recognition performance for each user without requiring complete system redesign, balancing reliability improvements with acceptable device complexity.
Solution Approach 2:
The system performs preliminary customization of recognition parameters and audio prompts based on user profiles before actual speech recognition begins. This preliminary action allows standardized deployment with enhanced performance by pre-configuring user-specific settings, reducing the need for complex real-time adjustments while improving reliability.
4Ease of operation
If user-specific customization is implemented, then user experience is improved, but data processing complexity and time increase
Solution Approach 1:
The system performs user-specific customization in advance by generating audio prompts and configuring recognition parameters before speech input begins. This preliminary action reduces processing time during actual speech recognition while still providing personalized user experience, as the computationally intensive customization work is completed beforehand.
Solution Approach 2:
The system applies customization locally to specific elements such as audio prompt generation and response formatting rather than overhauling the entire speech recognition pipeline. This localized approach improves user experience through personalization while minimizing the impact on overall processing time by leaving the core recognition engine unchanged.
Data Source
AI summary
An apparatus for speech recognition includes a user prompt playback unit configured to change a user prompt that induces utterance for speech recognition into a sound source and to play the sound source. The apparatus further includes a microphone detection signal extraction unit configured to extract a microphone detection signal when a user's speech is received as a speech signal through a microphone. The apparatus also includes a user prompt removal unit configured to remove the user prompt from the microphone detection signal. The apparatus further includes a speech recognition unit configured to recognize a speech based on a value from which the user prompt is removed. The apparatus also includes a response output unit configured to output a response related to the speech based on a result of recognizing the speech.