[PDF] Top 20 Aggregation via Set Partitioning for Natural Language Generation

... a set of hand-crafted rules that guide the aggregation process (Scott and de Souza, 1990; Hovy, 1990; Dalianis, 1999; Shaw, ...to aggregation within the context of a spoken dialog ...appropriate ... See full document

... tual language that is presented in the output win- ...tactic aggregation to improve the feedback, whereas DIAG-NLP2 is corpus-based and focuses on func- tional ... See full document

... by partitioning each of the datasets into training, val- idation and testing set in the ratio ...was set to be 80 for all cases, and the generators were trained with a 70% of dropout ...validation ... See full document

... The problem that is considered in this paper is as follows: Given a parallel corpus of multi- sentential texts and their underlying semantic rep- resentations along with the communicative goal of the text, can we learn ... See full document

... expression generation and aggregation) at once by treating microplanning as a search ...ing generation it tries to find an utterance which is in accordance with the constraints set by its ... See full document

... more natural than in the E2E challenge case, 2) there is a large amount of vari- ation in the dataset, and 3) the dataset was split in such a way that the paired set contains perfect matches between the MR ... See full document

... the set of nonterminals, O be the rules of the CFG, and I(c, o) returns a list of the nonterminals on the right hand side of the rule o and does not depend on ... See full document

... a set of previously completed plans can be treated as a training set: for each (state, action) pair considered, a feature vector Φ(s, a) is emit- ted, along with either the distance to the goal state or a ... See full document

... 3.4 Correlating Decisions with Text Features By allowing the generator to freely generate all possible output from a single input, we recorded a set of < trace, text > pairs ranging across the full variation ... See full document

... a set of sentences is sampled from a data structure created from an underlying gram- mar and ranked according to how well they meet the communicative ...the generation problem in a goal-directed ...This ... See full document

... one of the best-performing systems of the GIVE-1 Challenge. Baseline B, like the original “Austin” system, issues navigation instructions by precom- puting the shortest path from the IF’s current lo- cation to the ... See full document

... the set of all possible sets communicative goals for which the dialog manager requires realization are matched with a set of corresponding surface syntax ...latter set is input to FERGUS, which gen- ... See full document

... To get an idea of what the upper bound on ac- curacy is for this task, we tried applying the di- rect evidence method trained on both the train- ing data and the held-out test data. This gave an accuracy of approximately ... See full document

... Dutch word order uses multiple constructions (Kooij, 1978, pp. 33-36). It does not adhere to a standard like subject-verb-object (SVO) or subject- object-verb. Luckily, SimpleNLG is fairly flexible. It provides the user ... See full document

... These parameters have to be tuned for every pic- tograph language/NL pair. For Dutch, our tun- ing set consists of 50 manually translated mes- sages from the WAI-NOT corpus. We ran five tri- als of local ... See full document

... training set by removing pairs whose ground truth solution contains con- stants not mentioned in the question, as our model requires the constants to be copied from the ques- ...development set, but we ... See full document

... For example, consider the query “blue polo with purple stripes" issued to the Bing Shopping engine. Pages of results are returned with correctly matching products. Browsing through these, especially in a mobile or ... See full document

... 2013). We perform experiments at generating lan- guage at the word as well as character-level. The CMU−SE dataset consists of 44,016 sentences with a vocabulary of 3,122 words, while the Penn Treebank consists of 42,068 ... See full document

... text generation, the text − to − text approach is used to automat- ically summarize texts (Rotem, 2003) or opin- ions (Labb´e and Portet, 2012) expressed in nat- ural ...sentence aggregation, enumer- ative ... See full document

... We present our experimental results in Table 1 and 2. As shown, our model, NLG-LM, outperforms the baseline models in all 5 datasets. In E2E-NLG dataset, it achieves 2.2% higher BLEU score and 0.013 higher NIST score ... See full document