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地鐵運(yùn)營崗位應(yīng)急處置培訓(xùn)的語音識別研究
信息技術(shù)與網(wǎng)絡(luò)安全 6期
周 楊,錢雪軍
(同濟(jì)大學(xué) 電子與信息工程學(xué)院,上海 201804)
摘要: 地鐵交通運(yùn)營是一種整體性活動(dòng),離不開各部門間的協(xié)調(diào)配合,地鐵運(yùn)營崗位應(yīng)急處置培訓(xùn)系統(tǒng)應(yīng)用于多個(gè)崗位的聯(lián)合培訓(xùn)。該系統(tǒng)通過語音識別來實(shí)現(xiàn)模擬崗位間語音交互及對培訓(xùn)過程智能評價(jià)的功能。提出的語音識別方法可實(shí)現(xiàn)離線網(wǎng)絡(luò)下對地鐵培訓(xùn)專業(yè)術(shù)語的高識別精度,利用深度全序列卷積神經(jīng)網(wǎng)絡(luò)(DFCNN)和鏈接時(shí)序分類(CTC)構(gòu)建聲學(xué)模型,對應(yīng)急處置培訓(xùn)用語進(jìn)行整理并構(gòu)建專業(yè)術(shù)語庫,基于統(tǒng)計(jì)學(xué)構(gòu)建語言模型。實(shí)驗(yàn)結(jié)果表明,該語音識別方法能夠有效識別地鐵應(yīng)急處置培訓(xùn)用語,為地鐵運(yùn)營崗位人員的培訓(xùn)和考核提供更全面的評價(jià)指標(biāo)。
中圖分類號: U231.92;TP39
文獻(xiàn)標(biāo)識碼: A
DOI: 10.19358/j.issn.2096-5133.2022.06.012
引用格式: 周楊,錢雪軍. 地鐵運(yùn)營崗位應(yīng)急處置培訓(xùn)的語音識別研究[J].信息技術(shù)與網(wǎng)絡(luò)安全,2022,41(6):73-76,93.
Speech recognition research on emergency disposal training for subway operation positions
Zhou Yang,Qian Xuejun
(School of Electronic and Information Engineering, Tongji University, Shanghai 201804, China)
Abstract: Metro transportation operation is a holistic activity, and it is inseparable from the coordination and cooperation between various departments. The subway operation post emergency response training system is used for joint training of multiple posts. The system needs voice recognition to simulate the function of voice interaction between posts and intelligent evaluation of the training process. The speech recognition method proposed in this paper realizes high recognition accuracy of subway training terminology under offline network. Using deep fully convolutional neural network (DFCNN) and connectionist temporal classification (CTC) technology to build acoustic models, collating and constructing professional terminology bases for emergency disposal training terms, and building language models based on statistics and terminology banks. Experimental results show that the speech recognition technology can effectively identify training terms and provide more comprehensive evaluation indicators for the training and assessment of personnel in operational positions.
Key words : metro emergency disposal training; speech recognition; convolutional neural networks

0 引言

地鐵行車事故和突發(fā)事件嚴(yán)重影響了地鐵的正常運(yùn)營并威脅到了人民群眾的生命財(cái)產(chǎn)安全[1]。對于相應(yīng)的應(yīng)急預(yù)案而言,應(yīng)急預(yù)案演練的效果直接決定了應(yīng)急響應(yīng)的速度和應(yīng)急處置實(shí)施的有效性,其中應(yīng)急處置培訓(xùn)是應(yīng)急預(yù)案演練的重點(diǎn)。

目前的聯(lián)合培訓(xùn)系統(tǒng)需要所有培訓(xùn)崗位均為在崗狀態(tài),無法實(shí)現(xiàn)在聯(lián)合培訓(xùn)中的單崗位培訓(xùn)功能。因此在對各個(gè)崗位進(jìn)行應(yīng)急處置培訓(xùn)過程中需要模擬各個(gè)崗位之間的語音交互,實(shí)現(xiàn)單個(gè)崗位獨(dú)立培訓(xùn)時(shí)的智能互動(dòng),同時(shí)實(shí)現(xiàn)對培訓(xùn)過程的記錄與智能評價(jià)。語音識別是語音交互的基礎(chǔ)。目前,國內(nèi)外語音識別技術(shù)已經(jīng)趨于成熟,走向真正實(shí)用化[2],在日常對話等常見領(lǐng)域已達(dá)到實(shí)用要求,但是在地鐵等專業(yè)應(yīng)用領(lǐng)域的識別效果不佳[3]。

本文基于DFCNN-CTC框架提出新的語音識別聲學(xué)模型結(jié)構(gòu),以實(shí)現(xiàn)對應(yīng)急處置培訓(xùn)術(shù)語的高精度識別。實(shí)驗(yàn)表明,該語音識別模型可應(yīng)用于應(yīng)急處置培訓(xùn)系統(tǒng)中。




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作者信息:

周  楊,錢雪軍

(同濟(jì)大學(xué) 電子與信息工程學(xué)院,上海 201804)




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