文章基本信息

标题：Feature compensation based on independent noise estimation for robust speech recognition
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作者：Yong Lü ; Han Lin ; Pingping Wu 等
期刊名称：EURASIP Journal on Audio, Speech, and Music Processing
印刷版ISSN：1687-4714
电子版ISSN：1687-4722
出版年度：2021
卷号：2021
期号：1
页码：1
DOI：10.1186/s13636-021-00213-8
出版社：Hindawi Publishing Corporation
摘要：In this paper, we propose a novel feature compensation algorithm based on independent noise estimation, which employs a Gaussian mixture model (GMM) with fewer Gaussian components to rapidly estimate the noise parameters from the noisy speech and monitor the noise variation. The estimated noise model is combined with a GMM with sufficient Gaussian mixtures to produce the noisy GMM for the clean speech estimation so that parameters are updated if and only if the noise variation occurs. Experimental results show that the proposed algorithm can achieve the recognition accuracy similar to that of the traditional GMM-based feature compensation, but significantly reduces the computational cost, and thereby is more useful for resource-limited mobile devices.
关键词：Feature compensation ; Independent noise estimation ; Robust speech recognition ; Vector Taylor series