Incremental Speech Dictation with Real-Time Text Correction
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Solution Overview
Problem
Traditional Large Vocabulary Continuous Speech Recognition (LVCSR) systems require users to pause after each utterance, disrupting the flow of thought and providing incomplete or uncertain recognition results, as they decode complete sentences at once rather than in incremental portions.
Innovation Solution
A dictation module that interprets user utterances incrementally, providing real-time text output and allowing users to modify rendered text, with features like uncertainty-based delivery rates and adaptive models updated by user corrections, enabling continuous speech recognition without artificial pauses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the LVCSR system decodes complete utterances at once, then recognition accuracy can be improved through full context analysis, but user flow is disrupted by requiring pauses between utterances
Solution Approach 1:
The patent segments the complete utterance into incremental portions and processes them sequentially as they are spoken, rather than waiting for the complete utterance. This allows the system to provide intermediate recognition results for each segment while maintaining the ability to refine accuracy with additional context as the user continues speaking.
Solution Approach 2:
The system dynamically adjusts its processing mode between incremental recognition (for immediate feedback and user flow) and full context analysis (for improved accuracy). The recognition engine can operate in real-time on incoming segments while also performing comprehensive decoding when pauses are detected, combining both approaches adaptively.
2Ease of operation
If the system provides incremental recognition results in real-time, then user flow is maintained without pauses, but recognition accuracy may be reduced due to incomplete context
Solution Approach 1:
The system performs preliminary recognition on incremental portions as they are spoken, providing immediate intermediate results. When a pause is detected indicating the utterance is complete, the system then performs a final comprehensive decoding of the entire utterance to ensure maximum accuracy, using the preliminary results as a starting point.
Solution Approach 2:
The system provides continuous feedback to the user through intermediate recognition results during speech, allowing the user to see progress and confirm understanding. The system also uses feedback from detected pauses to trigger refined decoding, adjusting its processing based on user behavior patterns.
3Measurement precision
If the system waits for complete utterances before decoding, then recognition accuracy is improved through full context, but time is lost due to requiring user pauses
Solution Approach 1:
The system maintains continuous recognition processing throughout the user's speech without requiring pauses. It continuously decodes incoming speech segments and provides intermediate results, eliminating idle time where the user must pause. The comprehensive decoding is performed continuously in the background, ensuring accuracy is maintained without time loss.
Data Source
AI summary
A dictation module is described herein which receives and interprets a complete utterance of the user in incremental fashion, that is, one incremental portion at a time. The dictation module also provides rendered text in incremental fashion. The rendered text corresponds to the dictation module's interpretation of each incremental portion. The dictation module also allows the user to modify any part of the rendered text, as it becomes available. In one case, for instance, the dictation module provides a marking menu which includes multiple options by which a user can modify a selected part of the rendered text. The dictation module also uses the rendered text (as modified or unmodified by the user using the marking menu) to adjust one or more models used by the dictation model to interpret the user's utterance.