Study of Body-Conducted Speech Recognition for Support of Maritime Engine Operation
Study of Body-Conducted Speech Recognition for Support of Maritime Engine Operation
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支持船用发动机操作的体导语音识别研究
DOI：
10.5988/jime.39.263
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发表时间：
2004
期刊：
影响因子：
--
通讯作者：
Y. Murakami
中科院分区：
文献类型：
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作者：
S. Ishimitsu;M. Nakayama;Y. Murakami
语音识别系统最近已被引入到各种环境中，例如车辆仪表。语音识别在船舶轮机长系统中起着重要的作用。在这样的系统中，语音识别支持机舱控制，其中要求操作时的信噪比低于0分贝。在这样一个低信噪比的环境中，噪声信号可能被误判为语音，从而大大降低了识别率。因此，在低信噪比环境下工作的语音识别系统没有受到太多关注。这项研究的重点是一种使用身体传导信号的识别系统。这类信号很少受到背景噪声的影响，因此在机舱等低信噪比环境下可以预期较高的识别率。为了研究建立一个在信噪比低于0分贝的环境下工作的人体传导语音识别系统的可能性，我们调查了有效信号检测的位置，检查了从这些位置获得的特征向量，并在我校的大岛丸号训练船上用商业识别系统进行了简化的实验，以便我们可以验证其有效性。
Speech recognition systems have recently been introduced in a wide variety of environments such as vehicle instrumentation. Speech recognition plays an important role in ships' chief engineer systems. In such a system, voice recognition supports engine room controls, where operability at lower than 0 dB SNR is required. In such a low SNR environment, noise signals may be misjudged as speech, drastically decreasing the recognition rate. Speech recognition systems operating in low SNR environments have therefore not received much attention. This study focused on a recognition system that uses body-conducted signals. Such signals are seldom affected by background noise, so a high recognition rate can be expected in low SNR environments such as engine rooms. To examine the possibility of building a body-conducted speech recognition system operating under an SNR environment lower than 0 dB, we investigated locations for effective signal detection, examined feature vectors derived from those locations, and performed a simplified experiment with a commercial recognition system in our college's training ship, theOshima Maru, so that we could verify its effectiveness.