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ORIGINAL RESEARCH article

Front. Phys.
Sec. Physical Acoustics and Ultrasonics
Volume 12 - 2024 | doi: 10.3389/fphy.2024.1404503
This article is part of the Research Topic Mechanics/Acoustics Wave Regulation in Composite Structure View all articles

Research on Multi-Scenario Adaptive Acoustic Encoders Based on Neural Architecture Search

Provisionally accepted
Yiliang Wu Yiliang Wu 1,2Xuliang Luo Xuliang Luo 1,2Fengchan Guo Fengchan Guo 2Tinghui Lu Tinghui Lu 1,2Cuimei Liu Cuimei Liu 2*
  • 1 Faculty of Intelligent Manufacturing, Wuyi University, Jiangmen, China
  • 2 Jiangmen Power Supply Bureau, Guangdong Power Grid Co., Ltd., Jiangmen, China

The final, formatted version of the article will be published soon.

    This paper presents the Scene Adaptive Acoustic Encoder (SAAE) method, which is tailored to diverse acoustic environments for adaptive design. Hand-crafted acoustic encoders often struggle to adapt to varying acoustic conditions, resulting in performance degradation in end-to-end speech recognition tasks. To address this challenge, the proposed SAAE method learns the differences in acoustic features across different environments and accordingly designs suitable acoustic encoders.By incorporating neural architecture search technology, the effectiveness of the encoder design is enhanced, leading to improved speech recognition performance. Experimental evaluations on three commonly used Mandarin and English datasets (Aishell-1, HKUST, and SWBD) demonstrate the effectiveness of the proposed method. The SAAE method achieves an average error rate reduction of more than 5% compared with existing acoustic encoders, highlighting its capability to deeply analyze speech features in specific scenarios and design high-performance acoustic encoders in a targeted manner.

    Keywords: automatic speech recognition, Acoustic encoder, Acoustic features, Neural architecture search, Multi-scenario

    Received: 21 Mar 2024; Accepted: 25 Nov 2024.

    Copyright: © 2024 Wu, Luo, Guo, Lu and Liu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Cuimei Liu, Jiangmen Power Supply Bureau, Guangdong Power Grid Co., Ltd., Jiangmen, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.