Speech Recognition Confidence Adjustment for Breath-Stream Variability
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Solution Overview
Problem
Automatic Speech Recognition (ASR) systems face challenges in accurately recognizing speech from individuals with severe injuries or degenerative neuromuscular diseases, as their voice characteristics change throughout the breath stream, leading to inconsistent pronunciation and reduced system usability.
Innovation Solution
A speech recognition system that adjusts its confidence levels and matching algorithms based on the user's pulmonary state, specifically the amount of air remaining in the lungs, to differentiate between voiced and unvoiced sounds, thereby improving recognition accuracy for users with disabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a standard ASR algorithm is used to recognize speech, then the system can process utterances efficiently, but the recognition accuracy deteriorates for users with speech disabilities whose voice characteristics change throughout the breath stream
Solution Approach 1:
The system dynamically adjusts the ASR algorithm and confidence thresholds based on the detected breath stream state. Different algorithms are applied at different stages of the breath stream (initial exhalation vs. end of breath) to adapt to changing voice characteristics, thereby maintaining high recognition accuracy throughout the utterance while preserving processing efficiency.
Solution Approach 2:
The system changes key parameters including the confidence threshold and algorithm selection based on the breath stream state. When the user is at the end of their breath stream, the system lowers the confidence threshold and adjusts algorithm parameters to account for degraded voice quality, ensuring accurate recognition despite the changing acoustic characteristics.
2Ease of operation
If the ASR system uses a fixed confidence threshold for all utterances, then the system operation is simple, but the reliability of recognition deteriorates when voice characteristics change during the breath stream
Solution Approach 1:
The confidence threshold is dynamically adjusted based on the breath stream state detected by the system. During initial exhalation when voice characteristics are stable, a higher threshold is used. At the end of the breath stream when voice quality degrades, the threshold is automatically lowered to maintain reliable recognition, all without requiring complex manual configuration.
Solution Approach 2:
The system incorporates feedback from breath stream detection to continuously adjust confidence thresholds. The breath monitoring component provides real-time information about the user's pulmonary state, which feeds back to the ASR engine to modify recognition parameters, creating a closed-loop system that maintains high reliability adaptively.
3Device complexity
If the system assumes consistent speech characteristics throughout the breath stream, then the algorithm complexity is reduced, but the manufacturing precision of speech recognition deteriorates for disabled users
Solution Approach 1:
The breath stream is segmented into distinct phases (initial exhalation, middle phase, end of breath) with different acoustic characteristics. The system applies different ASR algorithms or parameter sets to each segment, allowing precise recognition adapted to the specific phase being processed while managing complexity through structured segmentation rather than entirely custom complex algorithms.
Solution Approach 2:
Specific algorithm parameters are changed based on breath stream phase detection. The system modifies acoustic model parameters, feature extraction settings, and confidence thresholds according to the detected pulmonary state, achieving high precision through parameter adaptation rather than requiring completely different complex algorithms for each scenario.
4Reliability
If the system queries the user frequently to confirm recognition accuracy, then the recognition reliability improves, but the ease of operation deteriorates
Solution Approach 1:
The frequency and timing of user confirmation queries are dynamically adjusted based on the breath stream state. During phases where the ASR system has high confidence (initial exhalation), fewer queries are prompted. During phases where accuracy is more uncertain (end of breath), the system strategically prompts for confirmation only when necessary, balancing reliability improvement with operational simplicity.
Solution Approach 2:
The system uses breath stream detection to self-regulate when user confirmation is needed, reducing unnecessary queries. By automatically detecting when recognition confidence may be compromised due to breath stream position, the system proactively manages its own accuracy verification needs, minimizing user burden while maintaining high reliability.
Data Source
AI summary
A speech recognition system is provided that, in one embodiment, includes an input 104 operable to receive voice utterances from a user, a speaker monitoring agent 132 operable to determine a pulmonary state of the user as a function of time, and a frame analyzer 120 operable to (i) determine a respective pulmonary state of the user at an approximate time when each of the voice utterances was made and (ii) process each of the voice utterance in a manner dependent upon the respective pulmonary state.