统计语言 meaning in Chinese
statistical language
Examples
- To retrieve information with more knowledge of language itself , statistical languages model for information retrieval was proposed a few years ago and develops fast
为了利用语言知识进行检索,近年来基于统计语言模型( slm - based )的信息检索得到了快速发展。 - An object - oriented chinese statistical language modeling toolkit is presented . the original trigram model is improved to have more capabilities of long dependency
论文对原有trigram的hmm统计模型进行改进，使其具有更多的长距依存能力，促进统计语言模型在中文自然语言处理领域的应用。 - Caption recognition feature extraction using wavelet transformation and the combination of statistical language model and hidden markov model methods finally achieved the identification of caption
基于统计机器学习的字幕识别提取小波变换的特征并使用隐马尔可夫模型和统计语言模型的识别技术相结合的机器学习方法，实现字幕文字的识别。 - As the character segmentation and recognition are doing synchronous , the wrong segmentation can be put right . and this permits the use of a lexicon directly within the lb algorithm rather than as a post - processing step
由于lbdtw算法将字符分割识别同步进行,字符分割是基于上一层字符识别结果的,分割错误可以根据识别信息得到纠正,并且统计语言信息可以融合到lb算法分层之间进行优化搜索。 - Neural networks are used more frequently in lossy data coding than in general lossless data coding , because standard neural networks must be trained off - line and they are too slow to be practical . in this thesis , statistical language model based on maximum entropy and neural networks are discussed particularly . then , an arithmetic coding algorithm based on maximum entropy and neural networks are proposed in this thesis
传统的人工神经网络数据编码算法需要离线训练且编码速度慢，因此通常多用于专用有损编码领域如声音、图像编码等，在无损数据编码领域应用较少，针对这种现状，本文详细地研究了最大熵统计语言模型和神经网络算法各自的特点，在此基础上提出了一种基于神经网络和最大熵原理的算术编码方法，这是一种自适应的可在线学习的算法，并具有精简的网络结构。