Abstract
Application of semantic speech recognition in designing of robust adaptive model for the DFIG wind energy conversion system is proposed in this paper. In order to reduce the labor intensity and environmental impact of the monitoring personnel and improve the speed and efficiency of the wind energy censuses, and reduce the cost of wind energy censuses, an intelligent wireless wind energy monitor with the speech analytic framework is designed, which is a convenient solution to these difficulties. In the speech recognition section, we have two major novelties. (1) In order to ensure the accuracy of substitution, this paper uses phonemes as the basic unit for the substitution of domain words. (2) The Euclidean distance in the feature space is equivalent to the cosine distance. In the test phase, complex similarity can be directly used to calculate scores. We use the Labview to implement the system, and the robustness test is done. The expeirment setting is based on the latest methodology. Through the experiment, after comparing with modern state-of-the-art methodologies, the performance of the proposed model is verified.
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10 October 2022
This article has been retracted. Please see the Retraction Notice for more detail: https://doi.org/10.1007/s10772-022-10005-w
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Funding
This funding was provided by Scientific Research Project of Anhui Education Department (Research of Intelligent Building Fire Detection Technology Based on Fuzzy Multi-sensor Information Fusion [Grant Number KJ2018JD13]).
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Zhang, H., Wu, C., Hao, J. et al. RETRACTED ARTICLE: Application of semantic speech recognition in designing of robust adaptive model for DFIG wind energy conversion system. Int J Speech Technol 24, 47–56 (2021). https://doi.org/10.1007/s10772-020-09719-6
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DOI: https://doi.org/10.1007/s10772-020-09719-6