Paper Group NANR 103
An Empirical Analysis of Formality in Online Communication. Chinese Preposition Selection for Grammatical Error Diagnosis. Delineating Fields Using Mathematical Jargon. CoCoGen - Complexity Contour Generator: Automatic Assessment of Linguistic Complexity Using a Sliding-Window Technique. Aspect Based Sentiment Analysis using Sentiment Flow with Loc …
An Empirical Analysis of Formality in Online Communication
| Title | An Empirical Analysis of Formality in Online Communication |
| Authors | Ellie Pavlick, Joel Tetreault |
| Abstract | This paper presents an empirical study of linguistic formality. We perform an analysis of humans{'} perceptions of formality in four different genres. These findings are used to develop a statistical model for predicting formality, which is evaluated under different feature settings and genres. We apply our model to an investigation of formality in online discussion forums, and present findings consistent with theories of formality and linguistic coordination. |
| Tasks | Automatic Writing, Knowledge Base Population, Natural Language Inference |
| Published | 2016-01-01 |
| URL | https://www.aclweb.org/anthology/Q16-1005/ |
| https://www.aclweb.org/anthology/Q16-1005 | |
| PWC | https://paperswithcode.com/paper/an-empirical-analysis-of-formality-in-online |
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Chinese Preposition Selection for Grammatical Error Diagnosis
| Title | Chinese Preposition Selection for Grammatical Error Diagnosis |
| Authors | Hen-Hsen Huang, Yen-Chi Shao, Hsin-Hsi Chen |
| Abstract | Misuse of Chinese prepositions is one of common word usage errors in grammatical error diagnosis. In this paper, we adopt the Chinese Gigaword corpus and HSK corpus as L1 and L2 corpora, respectively. We explore gated recurrent neural network model (GRU), and an ensemble of GRU model and maximum entropy language model (GRU-ME) to select the best preposition from 43 candidates for each test sentence. The experimental results show the advantage of the GRU models over simple RNN and n-gram models. We further analyze the effectiveness of linguistic information such as word boundary and part-of-speech tag in this task. |
| Tasks | Language Modelling |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/C16-1085/ |
| https://www.aclweb.org/anthology/C16-1085 | |
| PWC | https://paperswithcode.com/paper/chinese-preposition-selection-for-grammatical |
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Delineating Fields Using Mathematical Jargon
| Title | Delineating Fields Using Mathematical Jargon |
| Authors | Jevin West, Jason Portenoy |
| Abstract | |
| Tasks | Information Retrieval |
| Published | 2016-06-01 |
| URL | https://www.aclweb.org/anthology/W16-1508/ |
| https://www.aclweb.org/anthology/W16-1508 | |
| PWC | https://paperswithcode.com/paper/delineating-fields-using-mathematical-jargon |
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CoCoGen - Complexity Contour Generator: Automatic Assessment of Linguistic Complexity Using a Sliding-Window Technique
| Title | CoCoGen - Complexity Contour Generator: Automatic Assessment of Linguistic Complexity Using a Sliding-Window Technique |
| Authors | Str{"o}bel Marcus, Elma Kerz, Daniel Wiechmann, Stella Neumann |
| Abstract | We present a novel approach to the automatic assessment of text complexity based on a sliding-window technique that tracks the distribution of complexity within a text. Such distribution is captured by what we term {``}complexity contours{''} derived from a series of measurements for a given linguistic complexity measure. This approach is implemented in an automatic computational tool, CoCoGen {–} Complexity Contour Generator, which in its current version supports 32 indices of linguistic complexity. The goal of the paper is twofold: (1) to introduce the design of our computational tool based on a sliding-window technique and (2) to showcase this approach in the area of second language (L2) learning, i.e. more specifically, in the area of L2 writing. | |
| Tasks | |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/W16-4103/ |
| https://www.aclweb.org/anthology/W16-4103 | |
| PWC | https://paperswithcode.com/paper/cocogen-complexity-contour-generator |
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Aspect Based Sentiment Analysis using Sentiment Flow with Local and Non-local Neighbor Information
| Title | Aspect Based Sentiment Analysis using Sentiment Flow with Local and Non-local Neighbor Information |
| Authors | Shubham Pateria |
| Abstract | Aspect-level analysis of sentiments contained in a review text is important to reveal a detailed picture of consumer opinions. While a plethora of methods have been traditionally employed for this task, majority focus has been on analyzing only aspect-centered local information. However, incorporating context information from non-local aspect neighbors may capture richer structure in review text and enhance prediction. This may especially be helpful to resolve ambiguous predictions. The context around an aspect can be incorporated using semantic relations within text and inter-label dependencies in the output. On the output side, this becomes a structured prediction task. However, non-local label correlations are computationally heavy and intractable to infer for structured prediction models like Conditional Random Fields (CRF). Moreover, some prior intuition is required to incorporate non-local context. Thus, inspired by previous research on multi-stage prediction, we propose a two-level model for aspect-based analysis. The proposed model uses predicted probability estimates from first level to incorporate neighbor information in the second level. The model is evaluated on data taken from SemEval Workshops and Bing Liu{'}s review collection. It shows comparatively better performance against few existing methods. Overall, we get prediction accuracy in a range of 83-88{%} and almost 3-4 point increment against baseline (first level only) scores. |
| Tasks | Aspect-Based Sentiment Analysis, Sentiment Analysis, Structured Prediction |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/C16-1248/ |
| https://www.aclweb.org/anthology/C16-1248 | |
| PWC | https://paperswithcode.com/paper/aspect-based-sentiment-analysis-using |
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Imitation learning for language generation from unaligned data
| Title | Imitation learning for language generation from unaligned data |
| Authors | Gerasimos Lampouras, Andreas Vlachos |
| Abstract | Natural language generation (NLG) is the task of generating natural language from a meaning representation. Current rule-based approaches require domain-specific and manually constructed linguistic resources, while most machine-learning based approaches rely on aligned training data and/or phrase templates. The latter are needed to restrict the search space for the structured prediction task defined by the unaligned datasets. In this work we propose the use of imitation learning for structured prediction which learns an incremental model that handles the large search space by avoiding explicit enumeration of the outputs. We focus on the Locally Optimal Learning to Search framework which allows us to train against non-decomposable loss functions such as the BLEU or ROUGE scores while not assuming gold standard alignments. We evaluate our approach on three datasets using both automatic measures and human judgements and achieve results comparable to the state-of-the-art approaches developed for each of them. |
| Tasks | Imitation Learning, Structured Prediction, Text Generation |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/C16-1105/ |
| https://www.aclweb.org/anthology/C16-1105 | |
| PWC | https://paperswithcode.com/paper/imitation-learning-for-language-generation |
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Inconsistency Detection in Semantic Annotation
| Title | Inconsistency Detection in Semantic Annotation |
| Authors | Nora Hollenstein, Nathan Schneider, Bonnie Webber |
| Abstract | Inconsistencies are part of any manually annotated corpus. Automatically finding these inconsistencies and correcting them (even manually) can increase the quality of the data. Past research has focused mainly on detecting inconsistency in syntactic annotation. This work explores new approaches to detecting inconsistency in semantic annotation. Two ranking methods are presented in this paper: a discrepancy ranking and an entropy ranking. Those methods are then tested and evaluated on multiple corpora annotated with multiword expressions and supersense labels. The results show considerable improvements in detecting inconsistency candidates over a random baseline. Possible applications of methods for inconsistency detection are improving the annotation procedure as well as the guidelines and correcting errors in completed annotations. |
| Tasks | |
| Published | 2016-05-01 |
| URL | https://www.aclweb.org/anthology/L16-1629/ |
| https://www.aclweb.org/anthology/L16-1629 | |
| PWC | https://paperswithcode.com/paper/inconsistency-detection-in-semantic |
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How can we adapt generation to the user’s cognitive load?
| Title | How can we adapt generation to the user’s cognitive load? |
| Authors | Vera Demberg |
| Abstract | |
| Tasks | Text Generation |
| Published | 2016-09-01 |
| URL | https://www.aclweb.org/anthology/W16-6622/ |
| https://www.aclweb.org/anthology/W16-6622 | |
| PWC | https://paperswithcode.com/paper/how-can-we-adapt-generation-to-the-useras |
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The LetsRead Corpus of Portuguese Children Reading Aloud for Performance Evaluation
| Title | The LetsRead Corpus of Portuguese Children Reading Aloud for Performance Evaluation |
| Authors | Jorge Proen{\c{c}}a, Dirce Celorico, C, Sara eias, Carla Lopes, Fern Perdig{~a}o, o |
| Abstract | This paper introduces the LetsRead Corpus of European Portuguese read speech from 6 to 10 years old children. The motivation for the creation of this corpus stems from the inexistence of databases with recordings of reading tasks of Portuguese children with different performance levels and including all the common reading aloud disfluencies. It is also essential to develop techniques to fulfill the main objective of the LetsRead project: to automatically evaluate the reading performance of children through the analysis of reading tasks. The collected data amounts to 20 hours of speech from 284 children from private and public Portuguese schools, with each child carrying out two tasks: reading sentences and reading a list of pseudowords, both with varying levels of difficulty throughout the school grades. In this paper, the design of the reading tasks presented to children is described, as well as the collection procedure. Manually annotated data is analyzed according to disfluencies and reading performance. The considered word difficulty parameter is also confirmed to be suitable for the pseudoword reading tasks. |
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| Published | 2016-05-01 |
| URL | https://www.aclweb.org/anthology/L16-1125/ |
| https://www.aclweb.org/anthology/L16-1125 | |
| PWC | https://paperswithcode.com/paper/the-letsread-corpus-of-portuguese-children |
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Minimizing Regret on Reflexive Banach Spaces and Nash Equilibria in Continuous Zero-Sum Games
| Title | Minimizing Regret on Reflexive Banach Spaces and Nash Equilibria in Continuous Zero-Sum Games |
| Authors | Maximilian Balandat, Walid Krichene, Claire Tomlin, Alexandre Bayen |
| Abstract | We study a general adversarial online learning problem, in which we are given a decision set X’ in a reflexive Banach space X and a sequence of reward vectors in the dual space of X. At each iteration, we choose an action from X’, based on the observed sequence of previous rewards. Our goal is to minimize regret, defined as the gap between the realized reward and the reward of the best fixed action in hindsight. Using results from infinite dimensional convex analysis, we generalize the method of Dual Averaging (or Follow the Regularized Leader) to our setting and obtain upper bounds on the worst-case regret that generalize many previous results. Under the assumption of uniformly continuous rewards, we obtain explicit regret bounds in a setting where the decision set is the set of probability distributions on a compact metric space S. Importantly, we make no convexity assumptions on either the set S or the reward functions. We also prove a general lower bound on the worst-case regret for any online algorithm. We then apply these results to the problem of learning in repeated two-player zero-sum games on compact metric spaces. In doing so, we first prove that if both players play a Hannan-consistent strategy, then with probability 1 the empirical distributions of play weakly converge to the set of Nash equilibria of the game. We then show that, under mild assumptions, Dual Averaging on the (infinite-dimensional) space of probability distributions indeed achieves Hannan-consistency. |
| Tasks | |
| Published | 2016-12-01 |
| URL | http://papers.nips.cc/paper/6216-minimizing-regret-on-reflexive-banach-spaces-and-nash-equilibria-in-continuous-zero-sum-games |
| http://papers.nips.cc/paper/6216-minimizing-regret-on-reflexive-banach-spaces-and-nash-equilibria-in-continuous-zero-sum-games.pdf | |
| PWC | https://paperswithcode.com/paper/minimizing-regret-on-reflexive-banach-spaces-1 |
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The Karlsruhe Institute of Technology Systems for the News Translation Task in WMT 2016
| Title | The Karlsruhe Institute of Technology Systems for the News Translation Task in WMT 2016 |
| Authors | Thanh-Le Ha, Eunah Cho, Jan Niehues, Mohammed Mediani, Matthias Sperber, Alex Allauzen, re, Alex Waibel, er |
| Abstract | |
| Tasks | Machine Translation |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/W16-2314/ |
| https://www.aclweb.org/anthology/W16-2314 | |
| PWC | https://paperswithcode.com/paper/the-karlsruhe-institute-of-technology-systems-1 |
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Investigating Language Universal and Specific Properties in Word Embeddings
| Title | Investigating Language Universal and Specific Properties in Word Embeddings |
| Authors | Peng Qian, Xipeng Qiu, Xuanjing Huang |
| Abstract | |
| Tasks | Word Embeddings |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/P16-1140/ |
| https://www.aclweb.org/anthology/P16-1140 | |
| PWC | https://paperswithcode.com/paper/investigating-language-universal-and-specific |
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A Study of Reuse and Plagiarism in LREC papers
| Title | A Study of Reuse and Plagiarism in LREC papers |
| Authors | Gil Francopoulo, Joseph Mariani, Patrick Paroubek |
| Abstract | The aim of this experiment is to present an easy way to compare fragments of texts in order to detect (supposed) results of copy {&} paste operations between articles in the domain of Natural Language Processing (NLP). The search space of the comparisons is a corpus labeled as NLP4NLP gathering a large part of the NLP field. The study is centered on LREC papers in both directions, first with an LREC paper borrowing a fragment of text from the collection, and secondly in the reverse direction with fragments of LREC documents borrowed and inserted in the collection. |
| Tasks | |
| Published | 2016-05-01 |
| URL | https://www.aclweb.org/anthology/L16-1298/ |
| https://www.aclweb.org/anthology/L16-1298 | |
| PWC | https://paperswithcode.com/paper/a-study-of-reuse-and-plagiarism-in-lrec |
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Tweester at SemEval-2016 Task 4: Sentiment Analysis in Twitter Using Semantic-Affective Model Adaptation
| Title | Tweester at SemEval-2016 Task 4: Sentiment Analysis in Twitter Using Semantic-Affective Model Adaptation |
| Authors | Elisavet Palogiannidi, Athanasia Kolovou, Fenia Christopoulou, Filippos Kokkinos, Elias Iosif, Mal, Nikolaos rakis, Haris Papageorgiou, Shrikanth Narayanan, Alex Potamianos, ros |
| Abstract | |
| Tasks | Opinion Mining, Sentiment Analysis, Twitter Sentiment Analysis, Word Embeddings |
| Published | 2016-06-01 |
| URL | https://www.aclweb.org/anthology/S16-1023/ |
| https://www.aclweb.org/anthology/S16-1023 | |
| PWC | https://paperswithcode.com/paper/tweester-at-semeval-2016-task-4-sentiment |
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The Role of Modifier and Head Properties in Predicting the Compositionality of English and German Noun-Noun Compounds: A Vector-Space Perspective
| Title | The Role of Modifier and Head Properties in Predicting the Compositionality of English and German Noun-Noun Compounds: A Vector-Space Perspective |
| Authors | Sabine Schulte im Walde, Anna H{"a}tty, Stefan Bott |
| Abstract | |
| Tasks | Machine Translation |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/S16-2020/ |
| https://www.aclweb.org/anthology/S16-2020 | |
| PWC | https://paperswithcode.com/paper/the-role-of-modifier-and-head-properties-in |
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