[PDF] Top 20 Improving Language Models by Clustering Training Sentences

... The experimental results presented show that clustering increases the absolute success rate of unigram and bigram language modeling for a particular ATIS task by up to about 12%, and tha[r] ... See full document

... We have used the UPenn Treebank portion of the WSJ corpus to carry out our experiments. The UPenn Treebank contains 24 sections of hand- parsed sentences. We used section 00-20 for training our ... See full document

... of sentences with low quality (ac- cording to quality measures), the performance of the classifiers continues ...low-quality sentences may lead to models learn- ing incorrect ... See full document

... Table 1 lists the description lengths for training data from 1 to 32k and Table 2 shows the precision and cov- erage achieved by each method with this data. In these tables, we can see that our method works ... See full document

... selecting training data for sentence-level RNN language ...n-gram language models’ rapid training and query time, which often requires just a single pass over the training ... See full document

... Regression models fitted in R are evaluated using AIC (Akaike, ...statistical models learned from the given ...the models trained with documents whose unnatural language blocks are removed, ... See full document

... Before proceeding to the discussion of the three scenarios, this section clarifies some basic copyright law concepts. Texts and literary works. Most corpora employed in NLP consist of web pages, publications, articles, ... See full document

... A lot of previous research has focused on speeding up NNLM training. It usually aims at removing the computational dependency on V . Schwenk (2007) used a short list of frequent words such that a large number of ... See full document

... How do instance-based learning and N -gram completion compare in terms of computation time? The Viterbi beam search decoder is linear in the pre- diction length. The index-based retrieval algorithm is constant in the ... See full document

... generate sentences that are directly adapted to the reference set, thereby only improving a specific evaluation metric, such as Bleu? We address this issue in three ways, showing that the former is indeed ... See full document

... After training language models on different types of monolingual data ...English sentences and 23M Chinese sentences according to LM scores, since Chinese monolingual corpus provided by ... See full document

... the language model, we use a 2-layer monodirectional LSTM with state size 1000 and randomly initialized word embeddings of size ...the language mod- elling objective and size 8 for aspect and polarity ... See full document

... For the third and final variation of our system, we preprocess the tuning and testing sets in the source language by consulting the translation table cre- ated for the second variation. For each token in the ... See full document

... Quiz bowl is a trivia competition in which play- ers are asked four-to-six sentence questions about entities (e.g., authors, battles, or events). It is an ideal task to evaluate DAN s because there is prior test:1,821}. ... See full document

... For our self-training approach, we use the parse scores as confidence measure to select sentences. We observed that although the original parse score is the averaged value of a sequence of transi- tions of ... See full document

... texts. At the word level, this translates to assum- ing that there exist word pairs such that the pres- ence of the first word in the problem part pre- dicts the presence/absence of the second word in the solution part ... See full document

... We learn the parameters of our model by min- imizing the negative log-likelihood of the train- ing data, using the probability introduced in Eq. (1). We rely on automatic differentiation to com- pute the gradients, and ... See full document

... in language learning provide specific methods to increase learners’ awareness of their goals, motives, applied strategies and actions in the pursuit of systemic ... See full document

... As an application of our method, we use the pre- viously extracted dictionaries to on-line augment the phrase table of an SMT system and observe the translation performance on test sentences that contain OOV ... See full document

... existing clustering algorithms. IMSAT is utilized to make the clustering process easy and improves the accuracy and NMI score by using the training ...After training algorithm, the proposed ... See full document