Incremental Parsing for Interruptible State Detection in Conversational Agents
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Solution Overview
Problem
Conversational agents face challenges in accurately determining the end of a turn in human-computer dialog, relying on fixed thresholds for silence gaps and prosody, which can lead to latency and instability in response timing.
Innovation Solution
An incremental parsing method is employed, where input utterances are parsed against a grammar with multiple parallel parses, transitioning to an interruptible state when a complete sentence is formed, and a pause longer than a threshold (Tmin or Tmax) is detected, allowing for informed turn-taking decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If fixed threshold for silence gap is used to determine turn completion, then the system is simple to implement, but the response timing becomes unstable and latency increases
Solution Approach 1:
The system dynamically adjusts the pause threshold parameter based on parse likelihood scores. When syntactic and semantic completeness is detected with high confidence, the threshold is lowered to trigger earlier turn completion. This resolves the contradiction by making the threshold adaptive rather than fixed, improving response timing stability without requiring completely complex new mechanisms.
Solution Approach 2:
The turn completion detection transitions from a static fixed-threshold approach to a dynamic system that continuously evaluates parse likelihood and adjusts the effective threshold accordingly. The system adapts its sensitivity based on the confidence of syntactic and semantic analysis, allowing responsive behavior adjustment without structural complexity.
2Measurement precision
If incremental parsing with multiple parallel parses is used to detect turn completion, then the accuracy of turn detection is improved, but the computational complexity increases
Solution Approach 1:
The parsing process is segmented into incremental steps that process input tokens sequentially, maintaining multiple parallel parse hypotheses. Each parse is evaluated independently for syntactic and semantic completeness, allowing the system to detect turn completion points without requiring complete processing of the entire utterance. This segmentation enables accurate turn detection while managing computational load through progressive evaluation.
Solution Approach 2:
The system performs partial parsing actions by evaluating only the necessary syntactic and semantic features required to determine turn completion, rather than performing exhaustive analysis of all possible parses. When sufficient evidence of completeness is found in parallel parses, the system triggers turn completion without continuing full processing of all parse hypotheses, reducing unnecessary computational complexity.
3Reliability
If the system waits for complete sentence formation before responding, then the accuracy of response is improved, but the response latency increases
Solution Approach 1:
The system performs preliminary evaluation of syntactic and semantic completeness during incremental parsing, identifying potential turn completion points before the utterance is fully processed. By detecting when parallel parses indicate sufficient completeness with high likelihood, the system can trigger response preparation in advance, reducing latency while maintaining accuracy through pre-validation of sentence completeness.
Solution Approach 2:
The system uses feedback from parse likelihood scores to dynamically adjust turn completion detection. When parallel parses show high confidence in syntactic and semantic completeness, the feedback triggers earlier turn completion decisions. This feedback mechanism allows the system to balance accuracy and latency by responding sooner when confidence is high, without sacrificing response accuracy.
Data Source
AI summary
The technology disclosed relates to computer-implemented conversational agents and particularly to detecting a point in the dialog (end of turn, or end of utterance) at which the agent can start responding to the user. The technology disclosed provides a method of incrementally parsing an input utterance with multiple parses operating in parallel. The technology disclosed includes detecting an interjection point in the input utterance when a pause exceeds a high threshold, or detecting an interjection point in the input utterance when a pause exceeds a low threshold and at least one of the parallel parses is determined to be interruptible by matching a complete sentence according to the grammar. The conversational agents start responding to the user at a detected interjection point.