Background Speech Recognition Assistant Using Two-Stage Segmentation
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Solution Overview
Problem
Existing speech recognition systems require manual activation or trigger phrases, leading to inconvenience and intolerance of errors, as users are not always available to initiate queries, and may miss important contexts in conversations.
Innovation Solution
A two-stage speech recognition system where a first stage recognizer is always on, classifies acoustic input signals into pre-defined classifications, and triggers a second stage recognizer for more accurate processing, allowing responses to be determined and output based on ranking criteria without user initiation, using different speech recognition algorithms for each stage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If speech recognition is activated only by button press or trigger phrase, then power consumption is reduced and false positives are minimized, but user convenience deteriorates and important contexts may be missed
Solution Approach 1:
The speech recognition system is divided into two stages: a first stage recognizer that continuously monitors acoustic input with low computational resources, and a second stage recognizer that performs full speech recognition only when triggered by the first stage. This segmentation allows the system to maintain always-on functionality for user convenience while consuming minimal power during idle periods.
Solution Approach 2:
The first stage recognizer performs preliminary classification of acoustic input signals before activating the second stage recognizer. By pre-processing and filtering inputs that meet specific criteria (such as containing trigger phrases or reaching confidence thresholds), the system prepares potential candidates for full recognition in advance, reducing unnecessary activations and power consumption.
2Ease of operation
If speech recognition is always on in background mode, then user convenience is improved and contexts are not missed, but power consumption increases and errors may not be tolerated
Solution Approach 1:
The system segments recognition into continuous monitoring mode (first stage) and active recognition mode (second stage). The first stage operates continuously with minimal power consumption to detect relevant inputs, while the second stage activates only when needed, maintaining convenience while controlling power usage.
Solution Approach 2:
The system changes operational parameters dynamically: the first stage recognizer uses lower computational resources and simpler algorithms for continuous monitoring, while the second stage recognizer uses full resources only when triggered. This parameter adjustment allows always-on functionality without sustained high power consumption.
3Device complexity
If single stage speech recognition is used, then device complexity is reduced, but measurement precision and response accuracy deteriorate
Solution Approach 1:
The recognition system is segmented into two stages with different functional specializations. The first stage handles preliminary filtering and trigger detection, while the second stage performs comprehensive speech recognition. This segmentation improves overall accuracy without requiring a single overly complex recognizer to handle all tasks.
Solution Approach 2:
The first stage recognizer acts as an intermediary between the microphone and the second stage recognizer. It filters and classifies acoustic inputs, triggering the second stage only when appropriate conditions are met. This intermediary layer improves recognition accuracy by ensuring the second stage processes only relevant inputs while maintaining manageable system complexity.
Data Source
AI summary
In one embodiment, a method receives an acoustic input signal at a speech recognizer configured to recognize the acoustic input signal in an always on mode. A set of responses based on the recognized acoustic input signal is determined and ranked based on criteria. A computing device determines if the response should be output based on a ranking of the response. The method determines an output method in a plurality of output methods based on the ranking of the response and outputs the response using the output method if it is determined the response should be output.