[PDF] Top 20 Semantic Textual Similarity for MT evaluation
Has 10000 "Semantic Textual Similarity for MT evaluation" found on our website. Below are the top 20 most common "Semantic Textual Similarity for MT evaluation".
Semantic Textual Similarity for MT evaluation
... As mentioned before, the goal of the RTE task (Bentivogli et al., 2009) is determining whether the meaning of a hypothesis H can be inferred from a text T. Thus, TE is a directional task and we say that T entails H, if a ... See full document
7
Learning the Impact of Machine Translation Evaluation Metrics for Semantic Textual Similarity
... of MT evaluation metrics together with other lexi- cal and syntactic features to predict the semantic similarity scores in ...the evaluation metrics to the overall performance and how ... See full document
6
Accuracy and robustness in measuring the lexical similarity of semantic role fillers for automatic semantic MT evaluation
... phrasal similarity metrics. Although lexical similarity evaluation with all the met- rics can be done very quickly at low cost, they assume that a good translation shares the same lexical choices as ... See full document
8
Learning Semantic Textual Similarity from Conversations
... Meaning similarity be- tween sentences then can be obtained by compar- ing the sentence-level representations learned by such ...resulting similarity scores on the Semantic Textual ... See full document
11
Learning the Impact and Behavior of Syntactic Structure: A Case Study in Semantic Textual Similarity
... In this paper, we deploy three different approaches to exploit and evaluate the impact of syntactic structure in the STS task. We use a bag-of-word baseline which is the official baseline of STS task for the ... See full document
9
Cross lingual Learning of Semantic Textual Similarity with Multilingual Word Representations
... In single-source training, we also observe that certain source languages do not offer any gener- alisation over certain target languages. Interest- ingly, certain combinations of training/testing lan- guage pairs yield ... See full document
5
Probabilistic Soft Logic for Semantic Textual Similarity
... In this paper, we use the same combined logic- based and distributional framework as Beltagy et al., (2013) but replace Markov Logic Networks with Probabilistic Soft Logic (PSL) (Kimmig et al., 2012; Bach et al., 2013). ... See full document
10
A Preliminary Evaluation of the Impact of Syntactic Structure in Semantic Textual Similarity and Semantic Relatedness Tasks
... pairwise similarity, such as lexical similarity using taxonomies (WordNet (Fellbaum, 1998)) or distri- butional semantic models (LDA (Blei et ... See full document
7
Rule based vs Neural Net Approaches to Semantic Textual Similarity
... Carmen Banea, Samer Hassan, Michael Mohler, and Rada Mihalcea. 2012. Unt: A supervised synergistic approach to semantic text similarity. In Proceedings of the First Joint Conference on Lexical and ... See full document
6
Fully Automatic Semantic MT Evaluation
... based MT evaluation metric, MEANT, that outperforms all other commonly used auto- matic metrics in correlating with human judgment on translation ...via semantic frames than other evaluation ... See full document
10
Frequently Asked Questions Retrieval for Croatian Based on Semantic Textual Similarity
... The next step was to obtain the binary relevance judgments for each query. Annotating relevance for the complete FAQ database is not feasible, as the total number of query-FAQ pairs is too large. On the other hand, not ... See full document
10
If Sentences Could See: Investigating Visual Information for Semantic Textual Similarity
... dataset and the cross-lingual EN-ES N EWS -16 dataset, we also compare our results with the best-performing systems from the corresponding SemEval shared tasks. ˇSari´c et al. (2012) reach 88% correlation on MSRV ID , ... See full document
15
Identifying Prominent Arguments in Online Debates Using Semantic Textual Similarity
... external evaluation approach, which com- pares the hypothesized clusters against target ...cluster evaluation is a non-trivial task and there is no consensus on the best ... See full document
6
Semantic Textual Similarity in Quality Estimation
... In spite of these short-comings, this approach can be quite useful in settings where we wish to predict the quality of sentences within a very specific domain. One potential such scenario, would be post-editing tasks in ... See full document
13
Neural Networks for Semantic Textual Similarity
... The evaluation of these simple models for semantic textual similar- ity serves as the lower bound to compare all other models that have increased complexity in their ... See full document
10
Task Oriented Intrinsic Evaluation of Semantic Textual Similarity
... • Accuracy is a common evaluation measure for many tasks. However, as the STS scores are con- tinuously valued, it is unclear how to compute it. One option is to define arbitrary bins and check whether the human ... See full document
10
Fine grained Semantic Textual Similarity for Serbian
... of semantic textual similarity (STS) has gained in prominence in the last few years, annotated STS datasets for model training and evaluation, particularly those with fine-grained ... See full document
9
Correlation Coefficients and Semantic Textual Similarity
... into semantic tex- tual similarity has focused on constructing state-of-the-art embeddings using sophisti- cated modelling, careful choice of learning signals and many clever ...cosine similarity ... See full document
12
On the Robustness of Syntactic and Semantic Features for Automatic MT Evaluation
... Linguistic metrics based on syntactic and semantic information have proven very effective for Automatic MT Evaluation. However, no results have been presented so far on their performance when applied ... See full document
9
Neural Models for Detecting Binary Semantic Textual Similarity for Algerian and MSA
... Traditional models for detecting STS cannot be applied on such data because they require existing resources and tools, such as tokeniser, stemmer, PoS tagger, etc. to pre-process the data and ex- tract useful features ... See full document
10
Related subjects