Low Latency Audio Interface with Incremental Processing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current system architectures for voice-activated devices like Amazon Echo introduce temporal latencies between user requests and system responses, leading to delayed information delivery, which detracts from the user experience.
Innovation Solution
The system preprocesses output responses by applying automatic speech recognition and natural language understanding to determine the type of information requested, allowing it to generate partial responses before the user completes their query, using techniques like dynamic programming and phoneme sequencing to ensure smooth transitions, thereby reducing overall latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the system waits for the complete user request before processing, then processing accuracy is improved, but response time increases
Solution Approach 1:
The system performs preliminary processing on partial user requests as they are being spoken. The speech recognition engine processes audio data in real-time segments, and the natural language understanding engine begins interpreting intent before the user finishes speaking, thereby reducing overall response time while maintaining processing accuracy through iterative refinement.
Solution Approach 2:
The request processing is divided into segmented stages: audio capture in real-time segments, incremental speech recognition processing, progressive natural language understanding, and staged response generation. This segmentation allows the system to work on different portions of the request simultaneously at different processing stages, reducing the total time required while maintaining accuracy through multiple processing passes.
2Reliability
If the system processes the complete request before responding, then response accuracy is improved, but user engagement decreases
Solution Approach 1:
The system provides preliminary response elements during the user's speech. While the user is still speaking, the system displays preliminary results, suggestions, or partial answers that engage the user immediately, creating an interactive feel. The complete accurate response is then provided once processing is finished, maintaining both engagement and accuracy.
Solution Approach 2:
The system provides incremental feedback during request processing. As the speech recognition and natural language understanding engines process the user's input in real-time, the system displays intermediate results, confidence levels, or suggested interpretations, keeping the user engaged and informed throughout the processing rather than creating a black-box delay.
3Loss of time
If the system generates response elements before request completion, then response time is reduced, but processing complexity increases
Solution Approach 1:
The processing architecture is segmented into independent modular components: audio capture module, speech recognition engine, natural language understanding engine, response generation module, and output module. Each module processes specific segments of the request independently and passes results to the next module, allowing parallel processing that reduces response time while managing complexity through clear module boundaries and defined interfaces.
Solution Approach 2:
The system performs preliminary processing actions in advance where possible. The speech recognition engine begins transcribing audio as it is captured, the natural language understanding engine starts analyzing intent from partial transcripts, and the response generation module prepares template responses beforehand. These preliminary actions are refined and completed once full input is received, reducing overall processing time while distributing complexity across multiple preliminary processing stages.
Data Source
AI summary
Systems and methods for utilizing incremental processing of portions of output data to limit the time required to provide a response to a user request are provided herein. In some embodiments, portions of the user request for information can be analyzed using techniques such as automatic speech recognition (ASR), speech-to-text (STT), and natural language understanding (NLU) to determine the overall topic of the user request. One the topic has been determined, portions of the anticipated audio output data can be synthesized independently instead of waiting for the complete response. The synthesized portions can then be provided to the electronic device in anticipation of being output through one or more speakers on the electronic device, which speeds up the time that the response can be provided to the user.