Generate sentences from given words

    • [PDF File]Generating Text via Adversarial Training - Zhe Gan

      https://info.5y1.org/generate-sentences-from-given-words_1_668f05.html

      the length of the sentence. The first several words can be relatively reasonable, however the quality of sentence deteriorates quickly. In addition, the lengths of sentences generated from random latent representations could be difficult to control. In this paper we propose a framework to generate realistic sentences with adversarial training ...

      sentence generator input words


    • [PDF File]Automation of Question Generation From Sentences

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      that automates generation of questions from a sentence, given a sentence, the system, will generate all possible questions which this sentence contain these questions answers. Since the given sentence may be a complex sentence, the system will generate elementary sentences, from the input complex sentences, using a syntactic parser. A part of ...

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    • [PDF File]Learning to Generate Questions by LearningWhat not to Generate

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      structure of sentences for clue words prediction. To generate questions given an answer chunk and the predicted clue words distribution in an input sentence, we apply the Seq2Seq framework which contains our feature-rich sentence encoder and a decoder with attention and copy mechanism. The clue word

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    • [PDF File]Generating Sentences from Semantic Vector Space ...

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      meanings of words [2, 15, 14], phrases and sentences [18, 16, 12], and even full documents [13, 3]. However, there has not been much work in the reverse direction: given a single vector that represents some meaning, can we generate grammatically correct text that retains that meaning?

      sentence creator with your own words


    • [PDF File]Phrase-based Image Captioning

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      to generate descriptive sentences given a sample image. This model has a strong focus on the syn-tax of the descriptions. We train a purely bilinear model that learns a metric between an image rep-resentation (generated from a previously trained Convolutional Neural Network) and phrases that are used to described them. The system is then able to infer phrases from a given image sam-ple. Based ...

      create a sentence generator


    • [PDF File]Every Picture Tells a Story: Generating Sentences from Images

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      Every Picture Tells a Story: Generating Sentences from Images Ali Farhadi 1, Mohsen Hejrati 2, Mohammad Amin Sadeghi , Peter Young , Cyrus Rashtchian 1, Julia Hockenmaier , David Forsyth 1 Computer Science Department University of Illinois at Urbana-Champaign fafarhad2,pyoung2,crashtc2,juliahmr,dafg@illinois.edu

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    • [PDF File]Collecting Pairs of Word Senses and Their Context ...

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      To generate such type of questions, identifying the word sense of a target word in a context is crucial to create a correct choice in the context sentences. We propose a novel Backward method that utilizes the existing search engine API to obtain context sentences for a given target word sense and further applied

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    • [PDF File]Text Generation from Keywords

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      set of words that can be used to generate nat-ural sentences, but to give a set of headwords or center words that a speaker might want to express, and describe a model that can provide the complementary information needed to gen-erate natural sentences by using a target lan-guage corpus when given …

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    • Automatic Generation of Narrative Content for Digital Games

      grammatically correct sentences. It will go through several stages in order to generate text which looks natural (similar to text that would be generated by a human being to express the given concepts). According to (Dalianis, 1996), the stages of an NLG system are: • content determination (choosing what concepts to express),

      sentence generator input words


    • [PDF File]Towards Text Generation with Adversarially Learned Neural ...

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      3.3 Decoding Generated Sentence Vectors to Words Given generated or real sentences in their fixed-length latent space, we would like to train a model that maps these vectors back to their respective sentences. To this end, we train a conditional GRU language model that, for each sentence x, conditions on the sentence vector representation, h x, as

      sentence generator with specific words


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