Báo cáo khoa học: "Improving Language Model Size Reduction using Better Pruning Criteria" pptx

... Improving Language Model Size Reduction using Better Pruning Criteria Jianfeng Gao Microsoft Research, Asia Beijing, 100080, ... method of combining two pruning criteria in model pruning. Our results show that the combined criterion consistently leads to smaller models than the models pruned using either of the criteria ... n-gram model pruning. In the next se...

Ngày tải lên: 23/03/2014, 20:20

... calcu- lated by language modeling view features, but also been maximized with statistical methods. Therefore the imprecise cases caused by special distribution in language modeling approach ... terms in a query Q. Combining the Unigram Model with the Bigram Model: This is commonly implemented with interpolation in statistical language model- ing: ܲ ሺ ݐ ௜ିଵ ,ݐ ௜ | ݀ ሻ ൌ ߣ...

Ngày tải lên: 08/03/2014, 01:20

... model and it can be approximated with hidden Markov models (HMM). The last term is an IMT model as described in (Barrachina et al., 2009). Finally, P r(d|e p , f ) is a constrained language model. ... IBM1 and IBM2 models, and inverse IBM1-inv and IBM2-inv models with the inverse dictionary from Eq. 9. However, a more interesting set up than using lan- guage models or translation mod...

Ngày tải lên: 07/03/2014, 22:20

... that the feature model in Table 2 is an example fea- ture model and not the actual model employed in the parse experiments. The details or references for the English and German models are provided ... parsers we also em- ploy some language- specific settings. For English we use learner and parser settings, as well as feature model from the English pretrained MaltParser -model availab...

Ngày tải lên: 17/03/2014, 02:20

... the four models in- dividually, and when it is used for all four models simultaneously. We saw the most overall improve- ment when VB was used only for Model 1; using VB for all four models simultaneously ... For our training, we ran GIZA++ for five iterations each of Model 1, the HMM, Model 3, and Model 4. Variational Bayes was only used for Model 1. Figure 1 shows how VB, and dif...

Ngày tải lên: 23/03/2014, 14:20

... the complexity of inter- language correspondence modeling. We conduct experiments in the field of cross -language sentiment classification, employing English as source language, and German, French, ... Experiments We evaluate CL-SCL for the task of cross- language sentiment classification using English as source language and German, French, and Japanese as target languages. Special em...

Ngày tải lên: 23/03/2014, 16:20

... Supervised models are limited by the amount of annotated data avail- able for training. Such a model is useful only for languages in which annotated corpora are available. Because an unsupervised model ... forms at 75.6% accuracy. The reduction error from the unsupervised model presented here to the backed-off model is 13%. This is compa- rable to the 14.3% error reduction...

Ngày tải lên: 23/03/2014, 19:20

... that we finally need a language model p(ejle~-l), a translation model p(ej Id, Z) and a probability p(ejlEj). For p(ejle~ -1) we use a class-based polygram language model (Schukat-Talamazzini, ... improved technique in generating a STL using the WA in the EM- algorithm. We generated a STL using 10 EM- iterations for model 1 and 10 iterations for model 2q The wh...

Ngày tải lên: 08/03/2014, 05:21

... generative Bayesian model. This model assumes that each word in the lost language is composed of mor- phemes which were generated with latent coun- terparts in the known language. We model bilin- gual ... given a corpus in a lost language and a non- parallel corpus in a related language from the same language family. Our primary goal is to translate words in the unknown languag...

Ngày tải lên: 17/03/2014, 00:20

... word, all possible segmentations of the word are generated and ranked using the language model. The probabilities for the language model are learnt from a set of words that were segmented with the ... vowel-less letter-sequence. These problems can be solved by using a bi-gram language model to capture the morphotactic proper- ties of a particular language. Instead of simply pe...

Ngày tải lên: 17/03/2014, 04:20