后者包括一下事物，例如植入环境的传感器的网络坐标，以及便携式的电脑设备和带有时间的地理识别系统。
The later includes such things as coordinating webs of sensors embedded in the environment as well as wearable computing and real-time geographic systems.
本课题所研究的景物理解系统作为一种智能识别系统，可以实时对周围的景物环境变化做出反应。
Scenery understanding system, which this paper researched as a kind of intelligent recognition system, may respond to the change of the surrounding scenery by real time.
实验结果表明，这种方法不仅有明显的语音增强效果，且应用于噪声环境下的说话人识别系统时，能够提高系统的鲁棒性。
Experiments show that the new arithmetic not only has excellent effects on speech improvement but also has potential to improve robustness of a speaker recognition system in noisy environments.
提出了实验室环境下输电线路上障碍物的重要特征，并基于这些特征设计了一套障碍物自动识别系统。
The important features of obstacles on the power transmission line are proposed and an automatic obstacle-recognition system is designed based on these features.
开发了一高噪声环境下特定人孤立词的语音识别系统，讨论了系统性能的考核情况。
A robust speech recognition system in high noise environment is introduced and its performance is discussed in this paper.
人像识别系统采用国际领先的识别算法，具有高准确度、高速度的身份认证，对环境适应能力强等优点。
Face recognition system USES the world's leading recognition algorithm with advantages of high accuracy, high-speed authentication, strong ability to adapt to the environment and so on.
背景噪声的存在，使得说话人识别系统的训练环境和测试环境发生失配，导致系统性能发生急剧下降。
The background noise leads a mismatch between the training environment and testing environment, and degrades the performance of speaker identification system.
在当前的实验室环境下，很多识别系统已经能够达到很好的性能。
And now many mature systems have got fairly high speech recognition rate in laboratory.
但语音识别系统忽略语言的视觉特性，仅仅利用听觉特性，使得语音识别系统在噪声环境下，识别率大大下降。
However, audio-recognition system only USES the audio information of speech, and ignores the visual features of it. Under the noise circumstance, the recognition rate declines so much.
分析和提出了一套摄像头标定方案，使汽车车牌识别系统能在自然环境下获取清晰的图像，提高了汽车车牌识别系统随机捕获完整汽车图像的鲁棒性能。
A set of camera demarcation scheme was brought forward to capture the clear image in nature circumstance and improve the robust character of capturing full vehicle image in random for VNPRS.
一个对一般环境图像具有一定适应能力的人脸识别系统，需要一个鲁棒的、高效的、实时的人脸检测系统。
Face recognition system adapted to some general environmental image to some extent needs a Robust, high efficient and real-time face detection system.
在基于GMM的语种识别系统中，实际环境和个人因素一直是影响识别率提高的因素。
In GMM-based language identification system, the environment and individual characteristics are always the factors that influence the identification accuracy.
在基于GMM的语种识别系统中，实际环境和个人因素一直是影响识别率提高的因素。
In GMM-based the factors that influence language identification system, the environment and individual characteristics are always the identification accuracy.
为了使语音识别系统在不同噪声环境下仍能具有较好的性能，就需要采用各种方法来增强识别系统的鲁棒性。
In order to make the speech recognition system maintain the good performance under these noise conditions, we must use various methods to enhance the robustness of system.
语音识别系统的实用化，需要对噪声有很强的鲁棒性，而噪声环境下的端点检测对整个识别系统性能起着关键的作用。
While speech recognition system is put into use, it must be robust to noise. The endpoint detection in noisy background plays an important role in the whole recognition system.
为了使说话人识别系统在语音较短和存在噪声的环境下也具有较高的识别率，基于矢量量化识别算法，对提取的特征参数进行研究。
To improve the performance of speaker recognition in the condition of noise and little speech data, feature parameters were studied based on the Vector Quantization (VQ).
为了使说话人识别系统在语音较短和存在噪声的环境下也具有较高的识别率，基于矢量量化识别算法，对提取的特征参数进行研究。
To improve the performance of speaker recognition in the condition of noise and little speech data, feature parameters were studied based on the Vector Quantization (VQ).
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