Voice Interaction System for Noisy Environments
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Solution Overview
Problem
Noisy environments significantly impair the accuracy of computer-based speech recognition systems, leading to errors and unintended responses due to background noise interference, which current solutions often address inadequately by simply asking users to repeat commands.
Innovation Solution
A processor-based system that analyzes user interaction events, including low-quality voice transcription events and no-intent matching events from speech-to-text and natural language processing services, using confidence scores to determine appropriate responses, such as deferring actions or providing contextual help, to improve user experience in noisy conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the speech recognition system processes all voice inputs in noisy environments, then the system remains responsive to user commands, but the accuracy of speech recognition deteriorates due to background noise interference
Solution Approach 1:
The patent introduces an intermediary analysis layer that processes speech inputs before they are acted upon. This intermediary system evaluates multiple factors including transcription quality, confidence scores, and contextual relevance to filter out noise-induced false positives while preserving genuine user commands.
Solution Approach 2:
The system implements feedback mechanisms by analyzing the quality and confidence of speech transcriptions, then adjusting its response behavior accordingly. When speech quality is low or confidence scores are insufficient, the system withholds automatic responses, effectively using feedback to prevent erroneous actions triggered by background noise.
2Measurement precision
If the system asks users to repeat commands in noisy environments, then the accuracy of command recognition improves, but the user experience deteriorates due to increased interruptions
Solution Approach 1:
Instead of immediately requesting repetition at the first sign of noise, the system performs partial analysis of the speech input quality and confidence scores before deciding whether to ask for repetition. This selective approach avoids unnecessary interruptions while maintaining accuracy when needed.
Solution Approach 2:
The system performs preliminary evaluation of speech transcription quality and contextual relevance before acting on the input. By pre-assessing whether the speech is likely to be a genuine command or background noise, the system可以避免不必要的重复请求，从而在保持准确性的同时改善用户体验。
3Speed
If the system acts on low-quality transcriptions, then the responsiveness to user input improves, but the error rate increases due to misinterpretation of background noise
Solution Approach 1:
The system dynamically adjusts its response threshold based on real-time assessment of transcription quality and confidence scores. When speech quality is high, the system responds quickly; when quality is low, it withholds response until confidence is sufficient or the user repeats the command, creating a dynamic balance between speed and accuracy.
Data Source
AI summary
Providing contextual help in an interactive voice system includes receiving a plurality of user interaction events during a user interaction window, wherein each of the user interaction events comprises one of a low quality voice transcription event from a speech-to-text (STT) service or a no-intent matching event from a natural language processing (NLP) service and receiving a respective transcription confidence score from the STT service for each of the plurality of user interaction events. For a one of the plurality of user interaction events, a determination is made of how to respond to a user providing the user interaction events based on how many events comprise the plurality of events and the transcription confidence score for the one event; and then instructions are provided to cause the determined response to be presented to the user in accordance with the determination of how to respond.