Speech Recognition Input Gating for Accurate Utterance Endpoints
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Solution Overview
Problem
ASR systems struggle to accurately and promptly determine the endpoints of user utterances in real-time speech input, leading to inaccurate responses or perceived non-responsiveness due to premature or delayed processing.
Innovation Solution
An ASR system that identifies pauses in speech input, analyzing both verbal and non-verbal cues from sensors to determine the completion of an utterance before presenting it to the speech recognition engine, using a confidence-based threshold to ensure accurate and timely processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If a fixed time-out period is employed to determine the endpoint of an utterance, then the ASR system can process speech input in real-time, but the system may prematurely determine utterance completion during user pauses or disfluencies, leading to inaccurate responses
Solution Approach 1:
The system dynamically adjusts the time-out period based on detected speech patterns and pause characteristics. Instead of using a fixed time-out threshold, the system adapts the waiting period according to the specific context of each utterance, allowing it to respond quickly to clear, complete statements while patiently waiting for users who pause to think or correct themselves.
Solution Approach 2:
The system changes the parameter of time-out duration based on analyzed speech features. By monitoring speech rate, pause length, and utterance structure, the system modifies the time-out threshold to match the detected speech pattern, thereby improving both response speed and accuracy in different conversational contexts.
2Reliability
If the ASR system waits for several seconds to confirm utterance completion, then accuracy improves, but the system becomes perceived as non-responsive and delays processing
Solution Approach 1:
The system performs partial processing of the utterance while still waiting for potential continuation. Instead of completely waiting for the full time-out period before any processing begins, the system starts preliminary analysis earlier, allowing it to quickly confirm completion when the utterance is clear while still maintaining accuracy for more ambiguous cases.
Solution Approach 2:
The system performs preliminary analysis of speech patterns and pause characteristics during the waiting period. By analyzing speech features in real-time as the utterance unfolds, the system can make early determinations about utterance completion without requiring the full time-out duration, thus reducing perceived delay while maintaining accuracy.
3Reliability
If the ASR system uses a longer time-out period to accommodate disfluent speech, then utterance completeness improves, but the system delays processing and cannot accept additional speech input during the waiting period
Solution Approach 1:
The system segments the time-out period into multiple analysis intervals, evaluating speech patterns at different stages. This allows the system to identify utterance completion progressively rather than waiting for a single extended period, maintaining utterance completeness while reducing overall delay and enabling faster processing of subsequent inputs.
Data Source
AI summary
A method of presenting a signal to a speech recognition engine is disclosed. According to an example of the method, an audio signal is received from a user. A portion of the audio signal is identified, the portion having a first time and a second time. A pause in the portion of the audio signal, the pause comprising the second time, is identified. It is determined whether the pause indicates the completion of an utterance of the audio signal. In accordance with a determination that the pause indicates the completion of the utterance, the portion of the audio signal is presented as input to the speech recognition engine. In accordance with a determination that the pause does not indicate the completion of the utterance, the portion of the audio signal is not presented as input to the speech recognition engine.