… While language modeling is our task and hence test perplexity is a natural evaluation
metric, we also evaluate our model on word accuracy for speech recognition (section 4.3). …

… A number of methods have been explored to train and apply word embeddings using
continuous models for language. Collobert et al. (2008) learn embeddings in an unsupervised …

… do here, SMT systems rely on Continuous Space Language Models (CSLMs) or Translation
… as more efficient to train FeatureRich Translation systems. This property is especially rele…

… language model (LM) probabilities in the large vocabulary continuous speech recognition
(LVCSR) systems… LM could be further improved using feature-rich LMs like maximum entropy (…

… information relies on continuous word embeddings2 as … -art systems, they are used
alongside features of the broader … We are the first to apply neural language model embeddings …

… of +3.0 BLEU on top of a powerful, featurerich baseline which already includes a target-only …
lation direction of the languages, as well as the direction of the language model. We denote …

… We make use of the HPYLM methodology to build CLMs using … , along with the benefits of
feature-rich modeling, in addition to … language modeling in continuous space,” in Proc. Human …

… We take advantage of continuous space representation by … language model features: a
5-gram language model trained … by data-intensive and feature-rich statistical machine translation. …

… Thus, we combine the benefits of both morpheme level and feature rich modeling. We … -mixture
language modeling in continuous space,” in Proc. Human Language Technology …

… in various tasks, including language modeling (Mikolov et al., … In many cases, traditional
feature-rich systems are being … MT system after mapping sentences into continuous space with …