Work

Active Noise Cancellation With MEMS Resonant Microphone Array

Year: 2020

Type: article

Abstract: This paper presents active noise cancelation (ANC) based on MEMS resonant microphone array (RMA) which offers very high sensitivities (and thus very low noise floors) near resonance frequencies and also provides filtering in acoustic domain. The ANC is targeted to actively cancel out any sound between 5 - 9 kHz (above the speech range of 300 - 3,400 Hz). The ANC works best around the resonance frequencies of the resonant microphones where the sensitivities are high. The ANC has been implemented with analog inverter, digital phase compensator, digital adaptive filter, and deep learning, and shown to perform better with a digital adaptive filter for both RMA-based and flat-band-microphone-based ANC. At the same time, when the sound intensity over 5 - 9 kHz is low, RMA-based ANC with adaptive filter works the best among different approaches tested. Automatic speech recognition under different noises (of different intensity levels) has been tested with ANC. In all the tested cases, word error rate improves with ANC.

Source: Journal of Microelectromechanical Systems

DOI: 10.1109/jmems.2020.3011938

Authors: Hai Liu, Song Liu, Anton A. Shkel, Eun Sok Kim

Institutions: University of Southern California, Meta (United States)

Language: English

Topic: Advanced Adaptive Filtering Techniques

Subfield: Computational Mechanics

Field: Engineering

Domain: Physical Sciences

Open Access status: green

Funders: National Institutes of Health, National Institute on Deafness and Other Communication Disorders

Awards: G1985913882, G9000125908