However, said Atherton, "the creativity, expertise, and the recognition of importance is still dependent on human judgment."
尽管如此，阿瑟顿说，“创造力、专门技术以及重要的识别仍然依赖于人类的判断。”
F truth is the recognition of the systematic character of a certain kind of error, then it would be fully dependent on the prior existence of this error.
如果真理是，对一种错误的系统化字符的认可，那么它会完全依赖于这个错误的先前存在。
VQ (Vector Quantization) technique is widely used in text-dependent and text-independent speaker recognition systems.
矢量量化(VQ)技术在话者识别系统中得到了广泛的应用。
Combined with characteristics of Chinese speech language, this paper presents a speaker dependent and independent medium and small vocabulary isolated words recognition system based on TMS320VC5507.
本文结合汉语语音特点，在TMS320VC5507芯片上实现了高性能特定人与非特定人中小词汇量孤立词识别系统。
Based on this, a signer dependent large vocabulary sign language recognition system was designed and implemented.
在此基础上实现了大词汇量手语识别系统。
Using different feature vectors, the effect of the vocoders differs on speaker dependent continuous speech recognition and speaker independent connected digits recognition.
对于特定人连续语音识别系统和非特定人连接词识别系统，在使用不同的特征矢量时，不同编码器产生的识别效果有比较大的差异。
The following description describes the basic features of the voice recognition mechanism which is based on a speaker dependent is dated word recognition method.
下列叙述说明了以与授话人有关的分离词汇识别法为基础的语音识别机理的基本特点。
Because the FSV recognition framework employs the image coordinate of feature points, it is a way to viewpoint free sign language recognition from viewpoint dependent features.
由于是直接基于特征点的图像坐标进行识别，此框架提供了一种使用视角相关特征而实现视角无关手语识别的可能性。
Image segmentation is significant because all subsequent tasks such as feature extraction, object recognition are dependent on the quality of image segmentation.
图像在分割后的处理，如特征提取、目标识别等都依赖于图像的分割质量，因此具有十分重要的意义。
A discrete hidden Markov model based on the multiple vector quantization codebooks is used here for speaker-dependent discrete speech recognition in Noisy Environments.
本文介绍多码本离散隐马尔可夫模型用于含噪声语音识别的研究成果。
A discrete hidden Markov model based on the multiple vector quantization codebooks is used here for speaker-dependent discrete speech recognition in Noisy Environments.
本文介绍多码本离散隐马尔可夫模型用于含噪声语音识别的研究成果。
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