Жасырын айнымалылар моделі

. This paper presents an unsupervised approach for dialogue act (DA) classification. We used a latent variable model to compress the dimensions of the feature vector. We introduced a paraphraser …...

Conventional approaches to Chinese word segmentation treat the problem as a character- based tagging task. Recently, semi-Markov models have been applied to the problem, in- corporating features based on complete …...

Recently there has been substantial interest in using spectral methods to learn generative se- quence models like HMMs. Spectral meth- ods are attractive as they provide globally con- sistent estimates …...

Threaded discussion forums provide an im- portant social media platform. Its rich user generated content has served as an important source of public feedback. To automatically discover the viewpoints or …...

Document-level sentiment analysis can bene- fit from fine-grained subjectivity, so that sen- timent polarity judgments are based on the relevant parts of the document. While fine- grained subjectivity annotations are …...

We present two latent variable models for learning character types, or personas, in film, in which a persona is defined as a set of mixtures over latent lexical classes. These …...

Understanding the actionable outcomes of a dialogue requires effectively modeling situational roles of dialogue participants, the structure of the dialogue and the rele- vance of each utterance to an eventual …...

AbstractWe present MultiP (Multi-instance Learning Paraphrase Model), a new model suited to identify paraphrases within the short messages on Twitter. We jointly model paraphrase relations between word and sentence pairs …...

We propose a novel pipeline for translation into morphologically rich languages which consists of two steps: initially, the source string is enriched with target morphological features and then fed into …...

Most work on extracting parallel text from comparable corpora depends on linguistic re- sources such as seed parallel documents or translation dictionaries. This paper presents a simple baseline approach for …...

AbstractWe present a latent variable model for predicting the relationship between a pair of text sequences. Unlike previous auto-encoding–based approaches that consider each sequence separately, our proposed framework utilizes both …...

AbstractIn this work, we propose to model the interaction between visual and textual features for multi-modal neural machine translation (MMT) through a latent variable model. This latent variable can be …...

AbstractSupervised models of NLP rely on large collections of text which closely resemble the intended testing setting. Unfortunately matching text is often not available in sufficient quantity, and moreover, within …...

AbstractSemantic sentence embedding models encode natural language sentences into vectors, such that closeness in embedding space indicates closeness in the semantics between the sentences. Bilingual data offers a useful signal …...

AbstractThis paper proposes a simple and effective approach to address the problem of posterior collapse in conditional variational autoencoders (CVAEs). It thus improves performance of machine translation models that use …...

AbstractDespite the promising results of current cross-lingual models for spoken language understanding systems, they still suffer from imperfect cross-lingual representation alignments between the source and target languages, which makes the …...

AbstractAcross languages, multiple consecutive adjectives modifying a noun (e.g. “the big red dog”) follow certain unmarked ordering rules. While explanatory accounts have been put forward, much of the work done …...

AbstractWe propose an efficient inference procedure for non-autoregressive machine translation that iteratively refines translation purely in the continuous space. Given a continuous latent variable model for machine translation (Shu et …...

AbstractPast work on story generation has demonstrated the usefulness of conditioning on a generation plan to generate coherent stories. However, these approaches have used heuristics or off-the-shelf models to first …...