1. 基于领域知识的语音识别鲁棒性增强技术研究.
- Author
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王斐斐, 贲可荣, and 张 献
- Abstract
Due to the decrease in accuracy of speech recognition software in noisy environments, a robust enhancement method based on domain knowledge is proposed to ensure the safety of using speech control operations. Taking ship control as the application background, a domain knowledge graph is established for ship control. Ship control commands are extracted from nautical books and classic naval warfare film and television materials, and a Chinese speech dataset for ship control commands is constructed. A domain knowledge-embedded decoding method is proposed to correct the output control commands by calculating the matching degree between the recognition result and the domain knowledge graph. Experimental results show that compared with the current popular connection time sequence classification decoding method and attention mechanism-based decoding method, the proposed decoding method reduces the word error rate by 4.0% and 1.5% when recognizing noisy speech with a signal-tonoise ratio of 10dB and 20dB, respectively, and improves the accuracy of command recognition by 10.3% and 6.3%, respectively, improving the robustness of the speech recognition model in recognizing Chinese commands. [ABSTRACT FROM AUTHOR]
- Published
- 2023
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