Evidence map›Paper›PMID 40572333›Full record

ArticleMicromachines2025

A Piezoelectric Micromachined Ultrasonic Transducer-Based Bone Conduction Microphone System for Enhancing Speech Recognition Accuracy.

Chongbin Liu, Xiangyang Wang, Jianbiao Xiao, Jun Zhou, Guoqiang Wu

Abstract read
In one paragraph

Article in Micromachines, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Chongbin LiuThe Institute of Technological Sciences, Wuhan University, Wuhan 430072, China.ORCID 0000-0003-4839-008X
Xiangyang WangThe Institute of Technological Sciences, Wuhan University, Wuhan 430072, China.
Jianbiao XiaoSchool of Information and Communication Engineering, University of Electronic Science and Technology of China (UESTC), Chengdu 611731, China.
Jun ZhouSchool of Information and Communication Engineering, University of Electronic Science and Technology of China (UESTC), Chengdu 611731, China.
Guoqiang WuThe Institute of Technological Sciences, Wuhan University, Wuhan 430072, China.ORCID 0000-0003-3458-0595

Funding

Fundamental Research Funds for the Central Universities 2042025kf0028Hubei Provincial Science and Technology Research Project 2024BAB006National Natural Science Foundation of China 62322409
6 · The paper itself

Abstract

Speech recognition in noisy environments has long posed a challenge. Air conduction microphone (ACM), the devices typically used, are susceptible to environmental noise. In this work, a customized bone conduction microphone (BCM) system based on a piezoelectric micromachined ultrasonic transducer is developed to capture speech through real-time bone conduction (BC), while a commercial ACM is integrated for simultaneous capture of speech through air conduction (AC). The system enables simpler and more robust BC speech capture. The BC speech capture achieves a signal-to-noise amplitude ratio over five times greater than that of AC speech capture in an environment with a noise level of 68 dB. Instead of using only AC-captured speech, both BC- and AC-captured speech are input into a speech enhancement module. The noise-insensitive BC-captured speech serves as a speech reference to adapt the SE backbone of AC-captured speech. The two types of speech are fused, and noise suppression is applied to generate enhanced speech. Compared with the original noisy speech, the enhanced speech achieves a character error rate reduction of over 20%, approaching the speech recognition accuracy of clean speech. The results indicate that this speech enhancement method based on the fusion of BC- and AC-captured speech efficiently integrates the features of both types of speech, thereby improving speech recognition accuracy in noisy environments. This work presents an innovative system designed to efficiently capture BC speech and enhance speech recognition in noisy environments.

Indexed as

bone conduction microphonemicroelectromechanical systems (MEMS)piezoelectric micromachinedultrasonic transducer (PMUT)speech enhancement

Identifiers

PMID40572333
PMCPMC12195400

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.