Adaptive Multichannel Dereverberation for ASR Latency
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Solution Overview
Problem
Existing techniques for mitigating reverberation in audio signals for automated assistants suffer from latency and performance degradation, especially when the audio source is non-stationary, leading to poor automatic speech recognition and delayed responses.
Innovation Solution
An adaptive multichannel technique using an online and causal filter that updates and applies dereverberation to audio data in real-time, utilizing multiple microphones to mitigate reverberation and adapt to changes in the Room Impulse Response, while maximizing the source signal-to-reverberation ratio and compensating for spectral nulls.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional dereverberation techniques are used, then reverberation mitigation is achieved, but latency increases and response time is delayed
Solution Approach 1:
The system performs preliminary actions by continuously updating the Room Impulse Response (RIR) model during the utterance using causal filtering, so that when dereverberation is needed, the model is already prepared and updated, reducing the time required for processing
Solution Approach 2:
The system dynamically adapts the RIR model in real-time during the utterance using an online causal filter that continuously updates as new audio data arrives, allowing the system to maintain high dereverberation quality without waiting for the entire utterance to be captured
2Reliability
If traditional dereverberation techniques are used, then reverberation is reduced, but performance degrades when the audio source is non-stationary
Solution Approach 1:
The system employs a dynamic adaptive filter that continuously updates the RIR model during the utterance, allowing it to track and adapt to changes in the audio source characteristics in real-time, making it effective for non-stationary sources
Solution Approach 2:
The system uses feedback from the incoming audio signal to continuously update the RIR model through the causal filter, allowing the system to adapt to changing source characteristics by using the most recent audio information available
3Loss of information
If the entire spoken utterance is captured before processing, then complete audio data is available for dereverberation, but latency in generating responses increases
Solution Approach 1:
The system performs preliminary updates to the RIR model using audio data as it arrives, so that dereverberation processing can begin before the entire utterance is complete, reducing overall response time while maintaining processing quality
Solution Approach 2:
The system dynamically processes audio data in real-time as it arrives, continuously updating the RIR model and performing dereverberation on available data, allowing response generation to begin before the utterance is fully captured
Data Source
AI summary
Utilizing an adaptive multichannel technique to mitigate reverberation present in received audio signals, prior to providing corresponding audio data to one or more additional component(s), such as automatic speech recognition (ASR) components. Implementations disclosed herein are “adaptive”, in that they utilize a filter, in the reverberation mitigation, that is online, causal and varies depending on characteristics of the input. Implementations disclosed herein are “multichannel”, in that a corresponding audio signal is received from each of multiple audio transducers (also referred to herein as “microphones”) of a client device, and the multiple audio signals (e.g., frequency domain representations thereof) are utilized in updating of the filter—and dereverberation occurs for audio data corresponding to each of the audio signals (e.g., frequency domain representations thereof) prior to the audio data being provided to ASR component(s) and/or other component(s).