cache language model造句

The cache language models upon which many speech recognition systems now rely are examples of such statistical models.
The cache language model and other statistical language models that are used in natural language processing are also examples of applications of probability theory.
As a more specific example of an application, the cache language models and other statistical language models used in natural language processing to assign probabilities to the occurrence of particular words and word sequences do so by means of probability distributions.
The development of the cache language model has generated considerable interest among those concerned with computational linguistics in general and statistical natural language processing in particular : recently there has been interest in applying the cache language model in the field of statistical machine translation.
The development of the cache language model has generated considerable interest among those concerned with computational linguistics in general and statistical natural language processing in particular : recently there has been interest in applying the cache language model in the field of statistical machine translation.
It's difficult to find cache language model in a sentence. 用cache language model造句挺难的

There exist variants of the cache language model in which not only single words but also multi-word sequences that have occurred previously are assigned higher probabilities ( e . g ., if " San Francisco " occurred near the beginning of the text subsequent instances of it would be assigned a higher probability ).
The success of the cache language model in improving word prediction rests on the human tendency to use words in a " bursty " fashion : when one is discussing a certain topic in a certain context the frequency with which one uses certain words will be quite different from their frequencies when one is discussing other topics in other contexts.
If the system has a cache language model, " elephant " will still probably be misrecognized the first time it is spoken and will have to be entered into the text manually; however, from this point on the system is aware that " elephant " is likely to occur again the estimated probability of occurrence of " elephant " has been increased, making it more likely that if it is spoken it will be recognized correctly.