[PDF] Top 20 Stochastic Language Generation in Dialogue using Factored Language Models
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Stochastic Language Generation in Dialogue using Factored Language Models
... reranking models have been used for over a decade for language generation (Langkilde and Knight 1998); however, we do not know of any evaluation of their paraphrasing ...generate language with ... See full document
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Stochastic Language Generation in Dialogue using Recurrent Neural Networks with Convolutional Sentence Reranking
... n-gram language model (LM) to rerank a set of candidates gener- ated by a handcrafted ...each dialogue type and then reranked the generator outputs using a set of rules to produce the final ... See full document
10
Natural Language Generation for Spoken Dialogue System using RNN Encoder Decoder Networks
... the models on the Laptop domain with varied propor- tion of training data, starting from 10% to 100% (Figure 3), (iii) trained general models by merg- ing all the data from four domains together and tested ... See full document
10
Natural Language Generation as Planning Under Uncertainty for Spoken Dialogue Systems
... the Dialogue Manager ...level generation steps or actions, for example first to summarize all the items and then to recommend the highest ranking ... See full document
9
Multi task Learning for Natural Language Generation in Task Oriented Dialogue
... in language make the re- sponse rather ...natural language gen- eration (Wen et ...natural language processing increases these models’ ca- pacity to generate sophisticated human-like re- ... See full document
6
Optimising Natural Language Generation Decision Making For Situated Dialogue
... User models are based on the navigation level and content decisions made in a sequence of in- structions, so that different sequences, with a certain distribution, lead to different user model classifica- ... See full document
10
Stylistic Variation in Television Dialogue for Natural Language Generation
... Character models are composed of significant features with |z| ≥ 1. While using features with |z| ≥ 2 might be a bet- ter choice, our NLG engine can manipulate many features under |z| ≥ ... See full document
9
Multi domain Neural Network Language Generation for Spoken Dialogue Systems
... puted using a two-tailed Student’s t-test, between the model trained with full data (scrALL) and all ...recruited using AMT. We tested our models on two adaptation scenarios: lap- top to TV and TV to ... See full document
10
Stochastic Language Generation Using WIDL Expressions and its Application in Machine Translation and Summarization
... for generation (see Section ...for generation (Nederhof and Satta, ...-gram language models (Section ...distributions using log-linear ...WIDL-based generation system in two ... See full document
8
Neural based Natural Language Generation in Dialogue using RNN Encoder Decoder with Semantic Aggregation
... implemented using the Ten- sorFlow library (Abadi et ...by using early stopping as described in Sec- tion ...trained models can differ depend- ing on the initialization, we also report the results ... See full document
10
Phrase Based Statistical Language Generation Using Graphical Models and Active Learning
... natural language under- standing in the Hidden Vector State model (He and Young, ...of dialogue systems, Table 1 illustrates how the input dialogue act is first mapped to a set of stacks of semantic ... See full document
10
Portuguese text generation using factored language models
... text generation. Some of the alternatives to these models have been described in previous work (see ...both models of higher order and those using addi- tional ...text generation ... See full document
12
Crowdsourcing Language Generation Templates for Dialogue Systems
... extracted dialogue corpus contains phrases the system has generated, and crowd-workers con- struct alternates for these phrases, which can be plugged back into the system as crowd ... See full document
9
Using Factored Word Representation in Neural Network Language Models
... of factored representations to smaller mapping steps, which are modelled by translation probabilities from input factor to out- put factor or by generating probabilities of addi- tional output factors from ... See full document
9
Confidence Weighted Learning of Factored Discriminative Language Models
... for language modeling, where even human experts will argue about whether a given sentence is fluent or ...effective language models must be trained on large datasets, so the option of requiring ... See full document
6
Context-dependent factored language models
... Table 4 shows recognition results in word error rate (WER) for the first recognition pass with bigram and tri- gram language models with Good-Turing and modified Knesser-Ney smoothing and different ... See full document
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... generation - multilingual information retrieval - multilingual natural language interfaces - multilingual dialogue systems - multilingual message understanding systems - corpus-based and[r] ... See full document
7
The Karlsruhe Institute of Technology Translation Systems for the WMT 2012
... and language model ...the language model, source side context would also be valuable for the decoder when searching for the best translation ...source language context available we use a bilingual ... See full document
7
The language of emails: Is it resembling more the spoken language or the written language?
... This article dealt only with emails and due to personal reasons, as a limitation in this paper, no more samples of emails were included since the users did not provide any consent to include more samples of their ... See full document
6
Semi Supervised Neural Text Generation by Joint Learning of Natural Language Generation and Natural Language Understanding Models
... computed using the E2E challenge metrics script 2 with default ...learned using paired+unpaired methods shows significant superior performances than the paired ... See full document
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