Audio Processing Pipeline Verification via ASR Feedback
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Solution Overview
Problem
Existing automated speech recognition (ASR) systems face challenges in verifying the quality of audio processing pipeline results, particularly due to errors in language detection that can lead to further errors in subsequent processing tasks.
Innovation Solution
The proposed solution involves a method that applies a language identification (LID) model to audio content to obtain language predictions, followed by the application of ASR models based on these predictions to generate outputs. These outputs are then used to verify the audio processing results, ensuring accurate language identification and subsequent processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If language identification (LID) models are used to detect spoken language in audio content, then automation of speech recognition processes is improved, but errors in language detection occur leading to further errors in subsequent processing
Solution Approach 1:
The patent implements a feedback mechanism where ASR models process the audio content using the predicted language from LID, and the resulting ASR outputs are fed back to verify the LID prediction. If the ASR performance metrics (such as language score or word error rate) indicate poor performance, the system triggers re-detection or correction of the language identification, creating a closed-loop verification system that improves reliability while maintaining automation.
2Speed
If LID models trained on signal statistics are used for language detection, then processing speed is improved, but inaccurately identifying languages occurs
Solution Approach 1:
The system performs preliminary language detection using the fast LID model to obtain an initial language prediction, then uses this prediction to configure and run ASR models. The ASR processing serves as a preliminary verification step that can confirm or correct the initial LID prediction before final speech recognition results are produced, allowing the system to maintain speed while improving accuracy through staged processing.
Data Source
AI summary
A system and method for verifying audio processing pipeline results using automated speech recognition. Language identification is performed on audio content in order to identify languages being spoken in the audio content. Selections related to ASR, such as selecting the ASR models or the preprocessing steps to use for ASR, are made based on the identified languages. One or more ASR models are applied in an ASR process. Results related to ASR such as the languages used for ASR selections, the selected models, or the selected preprocessing steps, are verified based on outputs of the ASR models. The verification results may be used for subsequent processing, for example, by deciding whether ASR results should be used for subsequent audio processing.