ASR Latency Reduction via Multi-Pass Partial Results
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Automatic speech recognition (ASR) systems face significant latency issues due to high computational costs, which hinder user adoption as they often take longer than the duration of the speech to produce accurate transcripts, creating a trade-off between accuracy and speed.
Innovation Solution
The system employs multiple search passes to generate intermediate results, using a Quick Pass for initial low-latency output and subsequent passes for incremental accuracy improvements, with the results being displayed and updated in a user-friendly interface to provide usable text sooner.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If multiple search passes are performed to improve transcription accuracy, then manufacturing precision is improved, but loss of time increases
Solution Approach 1:
The patent segments the transcription process into multiple passes, where each pass processes different aspects of the speech signal. The first pass generates initial results quickly, while subsequent passes refine accuracy. This segmentation allows the system to deliver usable results at different time points, resolving the contradiction between speed and accuracy by providing tiered output quality.
Solution Approach 2:
The patent performs preliminary transcription actions in the first pass to establish baseline results before committing to longer processing times. By completing initial transcription quickly and then optionally refining it through additional passes, the system provides preliminary value to users immediately while maintaining the option to improve accuracy later, thus addressing both speed and accuracy requirements.
2Loss of time
If computational resources are increased to reduce latency, then loss of time is reduced, but use of energy increases
Solution Approach 1:
The patent implements dynamic resource allocation where computational resources are adjusted based on the specific needs of each transcription task and user requirements. The system can dynamically choose to perform one or multiple passes depending on factors such as speech complexity, user patience, and available resources, thereby optimizing the balance between latency reduction and energy consumption rather than using fixed high-resource allocation.
Data Source
AI summary
A system and method is provided for reducing latency for automatic speech recognition. In one embodiment, intermediate results produced by multiple search passes are used to update a display of transcribed text.