Paper Group NANR 47
A Dataset of Hindi-English Code-Mixed Social Media Text for Hate Speech Detection. Evaluation methodologies in Automatic Question Generation 2013-2018. Detecting Institutional Dialog Acts in Police Traffic Stops. Real-time Change Point Detection using On-line Topic Models. IIT Delhi at SemEval-2018 Task 1 : Emotion Intensity Prediction. Does Abilit …
A Dataset of Hindi-English Code-Mixed Social Media Text for Hate Speech Detection
| Title | A Dataset of Hindi-English Code-Mixed Social Media Text for Hate Speech Detection |
| Authors | Aditya Bohra, Deepanshu Vijay, Vinay Singh, Syed Sarfaraz Akhtar, Manish Shrivastava |
| Abstract | Hate speech detection in social media texts is an important Natural language Processing task, which has several crucial applications like sentiment analysis, investigating cyberbullying and examining socio-political controversies. While relevant research has been done independently on code-mixed social media texts and hate speech detection, our work is the first attempt in detecting hate speech in Hindi-English code-mixed social media text. In this paper, we analyze the problem of hate speech detection in code-mixed texts and present a Hindi-English code-mixed dataset consisting of tweets posted online on Twitter. The tweets are annotated with the language at word level and the class they belong to (Hate Speech or Normal Speech). We also propose a supervised classification system for detecting hate speech in the text using various character level, word level, and lexicon based features. |
| Tasks | Hate Speech Detection, Sentiment Analysis |
| Published | 2018-06-01 |
| URL | https://www.aclweb.org/anthology/W18-1105/ |
| https://www.aclweb.org/anthology/W18-1105 | |
| PWC | https://paperswithcode.com/paper/a-dataset-of-hindi-english-code-mixed-social |
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Evaluation methodologies in Automatic Question Generation 2013-2018
| Title | Evaluation methodologies in Automatic Question Generation 2013-2018 |
| Authors | Jacopo Amidei, Paul Piwek, Alistair Willis |
| Abstract | In the last few years Automatic Question Generation (AQG) has attracted increasing interest. In this paper we survey the evaluation methodologies used in AQG. Based on a sample of 37 papers, our research shows that the systems{'} development has not been accompanied by similar developments in the methodologies used for the systems{'} evaluation. Indeed, in the papers we examine here, we find a wide variety of both intrinsic and extrinsic evaluation methodologies. Such diverse evaluation practices make it difficult to reliably compare the quality of different generation systems. Our study suggests that, given the rapidly increasing level of research in the area, a common framework is urgently needed to compare the performance of AQG systems and NLG systems more generally. |
| Tasks | Question Generation, Text Generation |
| Published | 2018-11-01 |
| URL | https://www.aclweb.org/anthology/W18-6537/ |
| https://www.aclweb.org/anthology/W18-6537 | |
| PWC | https://paperswithcode.com/paper/evaluation-methodologies-in-automatic |
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Detecting Institutional Dialog Acts in Police Traffic Stops
| Title | Detecting Institutional Dialog Acts in Police Traffic Stops |
| Authors | Vinodkumar Prabhakaran, Camilla Griffiths, Hang Su, Prateek Verma, Nelson Morgan, Jennifer L. Eberhardt, Dan Jurafsky |
| Abstract | We apply computational dialog methods to police body-worn camera footage to model conversations between police officers and community members in traffic stops. Relying on the theory of institutional talk, we develop a labeling scheme for police speech during traffic stops, and a tagger to detect institutional dialog acts (Reasons, Searches, Offering Help) from transcribed text at the turn (78{%} F-score) and stop (89{%} F-score) level. We then develop speech recognition and segmentation algorithms to detect these acts at the stop level from raw camera audio (81{%} F-score, with even higher accuracy for crucial acts like conveying the reason for the stop). We demonstrate that the dialog structures produced by our tagger could reveal whether officers follow law enforcement norms like introducing themselves, explaining the reason for the stop, and asking permission for searches. This work may therefore inform and aid efforts to ensure the procedural justice of police-community interactions. |
| Tasks | Speech Recognition |
| Published | 2018-01-01 |
| URL | https://www.aclweb.org/anthology/Q18-1033/ |
| https://www.aclweb.org/anthology/Q18-1033 | |
| PWC | https://paperswithcode.com/paper/detecting-institutional-dialog-acts-in-police |
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Real-time Change Point Detection using On-line Topic Models
| Title | Real-time Change Point Detection using On-line Topic Models |
| Authors | Yunli Wang, Cyril Goutte |
| Abstract | Detecting changes within an unfolding event in real time from news articles or social media enables to react promptly to serious issues in public safety, public health or natural disasters. In this study, we use on-line Latent Dirichlet Allocation (LDA) to model shifts in topics, and apply on-line change point detection (CPD) algorithms to detect when significant changes happen. We describe an on-line Bayesian change point detection algorithm that we use to detect topic changes from on-line LDA output. Extensive experiments on social media data and news articles show the benefits of on-line LDA versus standard LDA, and of on-line change point detection compared to off-line algorithms. This yields F-scores up to 52{%} on the detection of significant real-life changes from these document streams. |
| Tasks | Change Point Detection, Time Series, Topic Models |
| Published | 2018-08-01 |
| URL | https://www.aclweb.org/anthology/C18-1212/ |
| https://www.aclweb.org/anthology/C18-1212 | |
| PWC | https://paperswithcode.com/paper/real-time-change-point-detection-using-on |
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IIT Delhi at SemEval-2018 Task 1 : Emotion Intensity Prediction
| Title | IIT Delhi at SemEval-2018 Task 1 : Emotion Intensity Prediction |
| Authors | Bhaskar Kotakonda, Prashanth Gowda, Brejesh Lall |
| Abstract | This paper discusses the experiments performed for predicting the emotion intensity in tweets using a generalized supervised learning approach. We extract 3 kind of features from each of the tweets - one denoting the sentiment and emotion metrics obtained from different sentiment lexicons, one denoting the semantic representation of the word using dense representations like Glove, Word2vec and finally the syntactic information through POS N-grams, Word clusters, etc. We provide a comparative analysis of the significance of each of these features individually and in combination tested over standard regressors avaliable in scikit-learn. We apply an ensemble of these models to choose the best combination over cross validation. |
| Tasks | Emotion Recognition, Sentiment Analysis |
| Published | 2018-06-01 |
| URL | https://www.aclweb.org/anthology/S18-1051/ |
| https://www.aclweb.org/anthology/S18-1051 | |
| PWC | https://paperswithcode.com/paper/iit-delhi-at-semeval-2018-task-1-emotion |
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Does Ability Affect Alignment in Second Language Tutorial Dialogue?
| Title | Does Ability Affect Alignment in Second Language Tutorial Dialogue? |
| Authors | Arabella Sinclair, Adam Lopez, C. G. Lucas, Dragan Gasevic |
| Abstract | The role of alignment between interlocutors in second language learning is different to that in fluent conversational dialogue. Learners gain linguistic skill through increased alignment, yet the extent to which they can align will be constrained by their ability. Tutors may use alignment to teach and encourage the student, yet still must push the student and correct their errors, decreasing alignment. To understand how learner ability interacts with alignment, we measure the influence of ability on lexical priming, an indicator of alignment. We find that lexical priming in learner-tutor dialogues differs from that in conversational and task-based dialogues, and we find evidence that alignment increases with ability and with word complexity. |
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| Published | 2018-07-01 |
| URL | https://www.aclweb.org/anthology/W18-5005/ |
| https://www.aclweb.org/anthology/W18-5005 | |
| PWC | https://paperswithcode.com/paper/does-ability-affect-alignment-in-second |
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Point process latent variable models of larval zebrafish behavior
| Title | Point process latent variable models of larval zebrafish behavior |
| Authors | Anuj Sharma, Robert Johnson, Florian Engert, Scott Linderman |
| Abstract | A fundamental goal of systems neuroscience is to understand how neural activity gives rise to natural behavior. In order to achieve this goal, we must first build comprehensive models that offer quantitative descriptions of behavior. We develop a new class of probabilistic models to tackle this challenge in the study of larval zebrafish, an important model organism for neuroscience. Larval zebrafish locomote via sequences of punctate swim bouts–brief flicks of the tail–which are naturally modeled as a marked point process. However, these sequences of swim bouts belie a set of discrete and continuous internal states, latent variables that are not captured by standard point process models. We incorporate these variables as latent marks of a point process and explore various models for their dynamics. To infer the latent variables and fit the parameters of this model, we develop an amortized variational inference algorithm that targets the collapsed posterior distribution, analytically marginalizing out the discrete latent variables. With a dataset of over 120,000 swim bouts, we show that our models reveal interpretable discrete classes of swim bouts and continuous internal states like hunger that modulate their dynamics. These models are a major step toward understanding the natural behavioral program of the larval zebrafish and, ultimately, its neural underpinnings. |
| Tasks | Latent Variable Models |
| Published | 2018-12-01 |
| URL | http://papers.nips.cc/paper/8289-point-process-latent-variable-models-of-larval-zebrafish-behavior |
| http://papers.nips.cc/paper/8289-point-process-latent-variable-models-of-larval-zebrafish-behavior.pdf | |
| PWC | https://paperswithcode.com/paper/point-process-latent-variable-models-of |
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Learning to Dodge A Bullet: Concyclic View Morphing via Deep Learning
| Title | Learning to Dodge A Bullet: Concyclic View Morphing via Deep Learning |
| Authors | Shi Jin, Ruiynag Liu, Yu Ji, Jinwei Ye, Jingyi Yu |
| Abstract | The bullet-time effect, presented in feature film ``The Matrix”, has been widely adopted in feature films and TV commercials to create an amazing stopping-time illusion. Producing such visual effects, however, typically requires using a large number of cameras/images surrounding the subject. In this paper, we present a learning-based solution that is capable of producing the bullet-time effect from only a small set of images. Specifically, we present a view morphing framework that can synthesize smooth and realistic transitions along extit{a circular view path} using as few as three reference images. We apply a novel cyclic rectification technique to align the reference images onto a common circle and then feed the rectified results into a deep network to predict its motion field and per-pixel visibility for new view interpolation. Comprehensive experiments on synthetic and real data show that our new framework outperforms the state-of-the-art and provides an inexpensive and practical solution for producing the bullet-time effects. | |
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| Published | 2018-09-01 |
| URL | http://openaccess.thecvf.com/content_ECCV_2018/html/shi_jin_Learning_to_Dodge_ECCV_2018_paper.html |
| http://openaccess.thecvf.com/content_ECCV_2018/papers/shi_jin_Learning_to_Dodge_ECCV_2018_paper.pdf | |
| PWC | https://paperswithcode.com/paper/learning-to-dodge-a-bullet-concyclic-view |
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The emergence of multiple retinal cell types through efficient coding of natural movies
| Title | The emergence of multiple retinal cell types through efficient coding of natural movies |
| Authors | Samuel Ocko, Jack Lindsey, Surya Ganguli, Stephane Deny |
| Abstract | One of the most striking aspects of early visual processing in the retina is the immediate parcellation of visual information into multiple parallel pathways, formed by different retinal ganglion cell types each tiling the entire visual field. Existing theories of efficient coding have been unable to account for the functional advantages of such cell-type diversity in encoding natural scenes. Here we go beyond previous theories to analyze how a simple linear retinal encoding model with different convolutional cell types efficiently encodes naturalistic spatiotemporal movies given a fixed firing rate budget. We find that optimizing the receptive fields and cell densities of two cell types makes them match the properties of the two main cell types in the primate retina, midget and parasol cells, in terms of spatial and temporal sensitivity, cell spacing, and their relative ratio. Moreover, our theory gives a precise account of how the ratio of midget to parasol cells decreases with retinal eccentricity. Also, we train a nonlinear encoding model with a rectifying nonlinearity to efficiently encode naturalistic movies, and again find emergent receptive fields resembling those of midget and parasol cells that are now further subdivided into ON and OFF types. Thus our work provides a theoretical justification, based on the efficient coding of natural movies, for the existence of the four most dominant cell types in the primate retina that together comprise 70% of all ganglion cells. |
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| Published | 2018-12-01 |
| URL | http://papers.nips.cc/paper/8150-the-emergence-of-multiple-retinal-cell-types-through-efficient-coding-of-natural-movies |
| http://papers.nips.cc/paper/8150-the-emergence-of-multiple-retinal-cell-types-through-efficient-coding-of-natural-movies.pdf | |
| PWC | https://paperswithcode.com/paper/the-emergence-of-multiple-retinal-cell-types |
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Remote Photoplethysmography Correspondence Feature for 3D Mask Face Presentation Attack Detection
| Title | Remote Photoplethysmography Correspondence Feature for 3D Mask Face Presentation Attack Detection |
| Authors | Si-Qi Liu, Xiangyuan Lan, Pong C. Yuen |
| Abstract | 3D mask face presentation attack, as a new challenge in face recognition, has been attracting increasing attention. Recently, remote Photoplethysmography (rPPG) is employed as an intrinsic liveness cue which is independent of the mask appearance. Although existing rPPG-based methods achieve promising results on both intra and cross dataset scenarios, they may not be robust enough when rPPG signals are contaminated by noise. In this paper, we propose a new liveness feature, called rPPG correspondence feature (CFrPPG) to precisely identify the heartbeat vestige from the observed noisy rPPG signals. To further overcome the global interferences, we propose a novel learning strategy which incorporates the global noise within the CFrPPG feature. Extensive experiments indicate that the proposed feature not only outperforms the state-of-the-art rPPG based methods on 3D mask attacks but also be able to handle the practical scenarios with dim light and camera motion. |
| Tasks | Face Presentation Attack Detection, Face Recognition |
| Published | 2018-09-01 |
| URL | http://openaccess.thecvf.com/content_ECCV_2018/html/Siqi_Liu_Remote_Photoplethysmography_Correspondence_ECCV_2018_paper.html |
| http://openaccess.thecvf.com/content_ECCV_2018/papers/Siqi_Liu_Remote_Photoplethysmography_Correspondence_ECCV_2018_paper.pdf | |
| PWC | https://paperswithcode.com/paper/remote-photoplethysmography-correspondence |
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Stylistic Chinese Poetry Generation via Unsupervised Style Disentanglement
| Title | Stylistic Chinese Poetry Generation via Unsupervised Style Disentanglement |
| Authors | Cheng Yang, Maosong Sun, Xiaoyuan Yi, Wenhao Li |
| Abstract | The ability to write diverse poems in different styles under the same poetic imagery is an important characteristic of human poetry writing. Most previous works on automatic Chinese poetry generation focused on improving the coherency among lines. Some work explored style transfer but suffered from expensive expert labeling of poem styles. In this paper, we target on stylistic poetry generation in a fully unsupervised manner for the first time. We propose a novel model which requires no supervised style labeling by incorporating mutual information, a concept in information theory, into modeling. Experimental results show that our model is able to generate stylistic poems without losing fluency and coherency. |
| Tasks | Machine Translation, Style Transfer |
| Published | 2018-10-01 |
| URL | https://www.aclweb.org/anthology/D18-1430/ |
| https://www.aclweb.org/anthology/D18-1430 | |
| PWC | https://paperswithcode.com/paper/stylistic-chinese-poetry-generation-via |
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Grounding language acquisition by training semantic parsers using captioned videos
| Title | Grounding language acquisition by training semantic parsers using captioned videos |
| Authors | C Ross, ace, Andrei Barbu, Yevgeni Berzak, Battushig Myanganbayar, Boris Katz |
| Abstract | We develop a semantic parser that is trained in a grounded setting using pairs of videos captioned with sentences. This setting is both data-efficient, requiring little annotation, and similar to the experience of children where they observe their environment and listen to speakers. The semantic parser recovers the meaning of English sentences despite not having access to any annotated sentences. It does so despite the ambiguity inherent in vision where a sentence may refer to any combination of objects, object properties, relations or actions taken by any agent in a video. For this task, we collected a new dataset for grounded language acquisition. Learning a grounded semantic parser {—} turning sentences into logical forms using captioned videos {—} can significantly expand the range of data that parsers can be trained on, lower the effort of training a semantic parser, and ultimately lead to a better understanding of child language acquisition. |
| Tasks | Language Acquisition, Semantic Parsing |
| Published | 2018-10-01 |
| URL | https://www.aclweb.org/anthology/D18-1285/ |
| https://www.aclweb.org/anthology/D18-1285 | |
| PWC | https://paperswithcode.com/paper/grounding-language-acquisition-by-training |
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Time-Resolved Light Transport Decomposition for Thermal Photometric Stereo
| Title | Time-Resolved Light Transport Decomposition for Thermal Photometric Stereo |
| Authors | Kenichiro Tanaka, Nobuhiro Ikeya, Tsuyoshi Takatani, Hiroyuki Kubo, Takuya Funatomi, Yasuhiro Mukaigawa |
| Abstract | We present a novel time-resolved light transport decomposition method using thermal imaging. Because the speed of heat propagation is much slower than the speed of light propagation, transient transport of far infrared light can be observed at a video frame rate. A key observation is that the thermal image looks similar to the visible light image in an appropriately controlled environment. This implies that conventional computer vision techniques can be straightforwardly applied to the thermal image. We show that the diffuse component in the thermal image can be separated and, therefore, the surface normals of objects can be estimated by the Lambertian photometric stereo. The effectiveness of our method is evaluated by conducting real-world experiments, and its applicability to black body, transparent, and translucent objects is shown. |
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| Published | 2018-06-01 |
| URL | http://openaccess.thecvf.com/content_cvpr_2018/html/Tanaka_Time-Resolved_Light_Transport_CVPR_2018_paper.html |
| http://openaccess.thecvf.com/content_cvpr_2018/papers/Tanaka_Time-Resolved_Light_Transport_CVPR_2018_paper.pdf | |
| PWC | https://paperswithcode.com/paper/time-resolved-light-transport-decomposition |
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A Multilingual Dataset for Evaluating Parallel Sentence Extraction from Comparable Corpora
| Title | A Multilingual Dataset for Evaluating Parallel Sentence Extraction from Comparable Corpora |
| Authors | Pierre Zweigenbaum, Serge Sharoff, Reinhard Rapp |
| Abstract | |
| Tasks | Machine Translation, Semantic Textual Similarity |
| Published | 2018-05-01 |
| URL | https://www.aclweb.org/anthology/L18-1605/ |
| https://www.aclweb.org/anthology/L18-1605 | |
| PWC | https://paperswithcode.com/paper/a-multilingual-dataset-for-evaluating |
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Alibaba Submission to the WMT18 Parallel Corpus Filtering Task
| Title | Alibaba Submission to the WMT18 Parallel Corpus Filtering Task |
| Authors | Jun Lu, Xiaoyu Lv, Yangbin Shi, Boxing Chen |
| Abstract | This paper describes the Alibaba Machine Translation Group submissions to the WMT 2018 Shared Task on Parallel Corpus Filtering. While evaluating the quality of the parallel corpus, the three characteristics of the corpus are investigated, i.e. 1) the bilingual/translation quality, 2) the monolingual quality and 3) the corpus diversity. Both rule-based and model-based methods are adapted to score the parallel sentence pairs. The final parallel corpus filtering system is reliable, easy to build and adapt to other language pairs. |
| Tasks | Machine Translation, Word Alignment |
| Published | 2018-10-01 |
| URL | https://www.aclweb.org/anthology/W18-6482/ |
| https://www.aclweb.org/anthology/W18-6482 | |
| PWC | https://paperswithcode.com/paper/alibaba-submission-to-the-wmt18-parallel |
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