Feedforward Active Noise Cancellation Using Adaptive Speech Prediction
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Solution Overview
Problem
Feedforward active noise cancellation systems face performance reduction due to the violation of causality constraints caused by signal propagation delays, especially in small headphones or systems with long latency, which complicates the generation of effective anti-noise signals for non-stationary speech.
Innovation Solution
A feedforward active noise cancellation system that includes reference and error microphones, loudspeakers, and adaptive filters, where a first filter minimizes residual errors based on primary and secondary transfer functions, and a second adaptive filter uses a linear predictor to compensate for processing and propagation delays exceeding the first propagation delay, employing a high-order sparse linear predictor and improved proportionate normalized least mean squares algorithm.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a fixed feedforward ANC filter is used, then the system structure is simple, but the performance is significantly reduced due to inability to compensate for propagation delays
Solution Approach 1:
The ANC system is divided into two separate filters: a first filter for general noise cancellation and a second filter specifically for compensating propagation delays. This segmentation allows each filter to specialize in one function, with the second filter addressing the causality constraint violation without complicating the overall system architecture.
Solution Approach 2:
The second filter acts as an intermediary component that processes the output of the first filter and compensates for the propagation delay between reference and error microphones. This intermediary filter restores causality by predicting future noise values, thereby improving performance without requiring a complete system redesign.
2Volume of moving object
If the propagation delay between loudspeaker and error microphone is longer than the reference to error microphone delay, then the system can handle small headphone sizes, but the causality constraint is violated requiring prediction
Solution Approach 1:
The second filter performs preliminary action by predicting future noise values based on past and present observations. This prediction compensates for the propagation delay, allowing the system to maintain causality even when the loudspeaker-to-error-microphone delay exceeds the reference-to-error-microphone delay, thus enabling compact headphone designs.
3Reliability
If adaptive algorithms are used to act as predictors, then the causality constraint can be compensated, but the system complexity increases
Solution Approach 1:
The system employs dynamic filter coefficients that adapt to changing acoustic environments. The second filter's coefficients are continuously updated to optimize the prediction of propagation delays, allowing the system to maintain causality compensation while adapting to different operating conditions without requiring overly complex algorithms.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This system effectively handles the causality constraint and the complex nature of speech, improving noise cancellation performance by aligning sound paths and compensating for delays, thereby enhancing the attenuation of ambient noise.
Implementation Method 1
ANC is based on the principle of acoustic superposition, such that an anti-noise signal with the same amplitude and opposite phase is generated by a secondary source (e.g., headphone loudspeaker) to cancel unwanted noise at the desired cancellation point
Data Source
AI summary
A feedforward active noise cancellation system comprising one or more reference microphones, one or more loudspeakers, one or more error microphones, a first filter, and a second and adaptive filter. The first filter is configured to filter a first input signal to minimize a residual error. The second and adaptive filter comprises a linear predictor of speech. The second and adaptive filter is configured to filter a second input signal based on predicted speech to compensate for a processing delay and a second propagation delay exceeding a first propagation delay.