Intent Prediction for Speech Utterance Processing
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Solution Overview
Problem
Conventional speech-based systems experience delays in processing user requests due to waiting for the end of an utterance before recognizing words and determining intent, leading to unnecessary idle time and delayed responses.
Innovation Solution
Implementing continuous intent prediction and processing of natural language utterances, where words are recognized and intents are predicted in real-time as the user speaks, allowing for parallel processing and pre-fetching of content based on predicted user requests before the end of the utterance is detected.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the system waits for end of utterance detection before processing, then processing accuracy is improved, but response time deteriorates
Solution Approach 1:
The system performs preliminary processing of speech portions as they are received, before the complete utterance is detected. This includes recognizing words, determining intents, and generating user requests in advance, so that when the utterance ends, the processing is already complete or near-complete, significantly reducing response time while maintaining accuracy through iterative refinement
Solution Approach 2:
The utterance is divided into multiple portions that are processed independently and in parallel. Each portion is recognized and analyzed separately, allowing the system to make progress on processing multiple segments simultaneously rather than waiting for the entire utterance, thus reducing overall processing time while maintaining accuracy through aggregation of segment results
2Productivity
If parallel processing of utterance portions is implemented, then productivity is improved, but system complexity increases
Solution Approach 1:
The processing system is segmented into multiple independent processing pipelines that handle different portions of the utterance in parallel. Each pipeline performs speech recognition, intent determination, and request generation independently, allowing simultaneous processing of multiple segments without requiring complex inter-pipeline coordination, thus improving productivity while keeping individual component complexity manageable
Solution Approach 2:
The system performs processing on partial utterances before the complete utterance is received. User requests and responses can be generated based on incomplete information, and then refined or corrected as additional portions are processed. This approach increases productivity by not waiting for complete input, while the complexity is managed through iterative refinement rather than requiring perfect complete-state processing
Data Source
AI summary
In certain implementations, intent prediction is provided for a natural language utterance based on a portion of the natural language utterance prior to a system detection of an end of the natural language utterance. In some implementations, a first portion of a natural language utterance of a user may be received. Speech recognition may be performed on the first portion of the natural language utterance to recognize one or more words of the first portion of the natural language utterance. Context information for the natural language utterance may be obtained. Prior to a detection of an end of the natural language utterance, a first intent may be predicted based on the one or more words of the first portion and the context information. One or more user requests may be determined based on the first predicted intent.