[PDF] Top 20 Topic Adaptation for Lecture Translation through Bilingual Latent Semantic Models
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Topic Adaptation for Lecture Translation through Bilingual Latent Semantic Models
... language models for both the source and target language and thus can be used for language model adaptation through MDI in a similar manner as outlined in Fed- erico ...Another bilingual LSA ... See full document
9
Topic Models for Dynamic Translation Model Adaptation
... underlying latent topics of the documents (Blei et al., 2003). Topic modeling has received some use in SMT, for in- stance Bilingual LSA adaptation (Tam et ...a bilingual topic ... See full document
5
Learning Topic Representation for SMT with Neural Networks
... various semantic con- cepts embedded in a collection of ...on topic-based translation modeling in- clude topic-specific lexicon translation models (Zhao and Xing, 2006; Zhao and ... See full document
11
Bilingual LSA Based LM Adaptation for Spoken Language Translation
... (LM) adaptation based on bilingual Latent Semantic Analysis ...enables latent topic distributions to be efficiently transferred across languages by enforcing a one-to-one ... See full document
8
Translation Model Adaptation for Statistical Machine Translation with Monolingual Topic Information
... with translation model adap- tation by making use of the topical context, so let us take a look at the recent research developmen- t on the application of topic models in ...each bilingual ... See full document
10
Topic-based Multi-Document Summarization with Probabilistic Latent Semantic Analysis
... based on the identification of topics (or thematic foci) to construct generic or query-focused summaries. Of- ten, thematic features rely on identifying and weight- ing important keywords [21], or creating topic ... See full document
6
Semantic Language Models for Topic Detection and Tracking
... space models (Salton et al., 1975) and the more recent language models (Ponte and Croft, 1998) tend to ignore any semantic information and consider only word-tokens or word-stems as basic ... See full document
6
Latent Domain Phrase based Models for Adaptation
... Phrase-based models directly trained on mix-of-domain corpora can be ...phrase-based models with a latent domain variable and present a novel method for adapting them to an in-domain task rep- ... See full document
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Incremental Topic Based Translation Model Adaptation for Conversational Spoken Language Translation
... the topic(s) of discussion, and to deploy contextually appropriate translation phrase ...the translation ‘drogas’ (illegal drugs) will predominate in a law enforce- ment ... See full document
5
Improving Topic Models with Latent Feature Word Representations
... Unlike the document clustering task, the document classification task evaluates the distribution over topics for each document. Following Lacoste-Julien et al. (2009), Lu et al. (2011), Huh and Fien- berg (2012) and Zhai ... See full document
16
Construction of Chunk-Aligned Bilingual Lecture Corpus for Simultaneous Machine Translation
... Hong-Kwang Kuo, Wei zhong Zhu, Yonggang Deng, Charles Prosser, Wei Zhang, and Laurent Besacier. 2006. IBM Mastor System: Multilingual automatic speech-to- speech translator. In Proceedings of the 1st International ... See full document
6
Deterministic Annealing
... – Probabilistic Latent Semantic Analysis with Deterministic Annealing DA-PLSA as alternative to Latent Dirichlet Allocation typical informational retrieval/global inference topic model h[r] ... See full document
56
Incorporating topic information into semantic analysis models
... the topic with phrases which have been assigned favorability values are described in order to take advantage of situations in which the topic of the text may be explicitly ... See full document
5
Latent Semantic Analysis Models on Wikipedia and TASA
... Latent Semantic Analysis (LSA) is “a theory and method for extracting and representing the contextual-usage meaning of words by statistical computations applied to a large corpus of text” (Landauer at ... See full document
6
Cache Augmented Latent Topic Language Models for Speech Retrieval
... trieval. Topic models such as Latent Dirichlet Al- location (LDA) (Blei et ...Probabilistic Latent Semantic Analysis (PLSA) (Hofmann, 2001) are used to the augment the document-specific ... See full document
8
Reddit Temporal N gram Corpus and its Applications on Paraphrase and Semantic Similarity in Social Media using a Topic based Latent Semantic Analysis
... and semantic text similarity (Blacoe and Lapata, 2012; Madnani et ...explicit semantic space (Hassan and Mihalcea, 2011), vector-based similarity (Milajevs et ... See full document
12
An Empirical Study on the Effect of Negation Words on Sentiment
... Note that depending on different purposes, p sen 1 can take the value of the automatically predicted sentiment distribution obtained in forward propa- gation, the gold sentiment annotation of node p 1 , or even other ... See full document
10
Latent Variable Models for Semantic Orientations of Phrases
... the semantic orientations of phrases on the basis of the plus/minus attribute val- ues and the positive/negative attribute values of the component ...phrase-level semantic orien- ... See full document
8
Factorization of Latent Variables in Distributional Semantic Models
... factorized models, it also raises additional interesting research ques- ...prove models that have been trained on smaller data sets? Does it also hold for non-Gaussian factorization like Non-negative Matrix ... See full document
5
Aggregating Continuous Word Embeddings for Information Retrieval
... between topic models on dis- crete word occurrences such as PLSA/LDA and the proposed model for continuous word embed- ...generative models include a latent variable which indicates which ... See full document
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