Paper Group NANR 173
Improving event prediction by representing script participants. Large-scale Multitask Learning for Machine Translation Quality Estimation. Vision and Feature Norms: Improving automatic feature norm learning through cross-modal maps. Probabilistic Models for Learning a Semantic Parser Lexicon. Dialogue Act Classification in Domain-Independent Conver …
Improving event prediction by representing script participants
| Title | Improving event prediction by representing script participants |
| Authors | Simon Ahrendt, Vera Demberg |
| Abstract | |
| Tasks | |
| Published | 2016-06-01 |
| URL | https://www.aclweb.org/anthology/N16-1067/ |
| https://www.aclweb.org/anthology/N16-1067 | |
| PWC | https://paperswithcode.com/paper/improving-event-prediction-by-representing |
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Large-scale Multitask Learning for Machine Translation Quality Estimation
| Title | Large-scale Multitask Learning for Machine Translation Quality Estimation |
| Authors | Kashif Shah, Lucia Specia |
| Abstract | |
| Tasks | Machine Translation |
| Published | 2016-06-01 |
| URL | https://www.aclweb.org/anthology/N16-1069/ |
| https://www.aclweb.org/anthology/N16-1069 | |
| PWC | https://paperswithcode.com/paper/large-scale-multitask-learning-for-machine |
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Vision and Feature Norms: Improving automatic feature norm learning through cross-modal maps
| Title | Vision and Feature Norms: Improving automatic feature norm learning through cross-modal maps |
| Authors | Luana Bulat, Douwe Kiela, Stephen Clark |
| Abstract | |
| Tasks | Image Retrieval, Text Simplification |
| Published | 2016-06-01 |
| URL | https://www.aclweb.org/anthology/N16-1071/ |
| https://www.aclweb.org/anthology/N16-1071 | |
| PWC | https://paperswithcode.com/paper/vision-and-feature-norms-improving-automatic |
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Probabilistic Models for Learning a Semantic Parser Lexicon
| Title | Probabilistic Models for Learning a Semantic Parser Lexicon |
| Authors | Jayant Krishnamurthy |
| Abstract | |
| Tasks | Semantic Parsing |
| Published | 2016-06-01 |
| URL | https://www.aclweb.org/anthology/N16-1074/ |
| https://www.aclweb.org/anthology/N16-1074 | |
| PWC | https://paperswithcode.com/paper/probabilistic-models-for-learning-a-semantic |
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Dialogue Act Classification in Domain-Independent Conversations Using a Deep Recurrent Neural Network
| Title | Dialogue Act Classification in Domain-Independent Conversations Using a Deep Recurrent Neural Network |
| Authors | Hamed Khanpour, Guntak, Nishitha la, Rodney Nielsen |
| Abstract | In this study, we applied a deep LSTM structure to classify dialogue acts (DAs) in open-domain conversations. We found that the word embeddings parameters, dropout regularization, decay rate and number of layers are the parameters that have the largest effect on the final system accuracy. Using the findings of these experiments, we trained a deep LSTM network that outperforms the state-of-the-art on the Switchboard corpus by 3.11{%}, and MRDA by 2.2{%}. |
| Tasks | Dialogue Act Classification, Dialogue Interpretation, Machine Translation, Speech Recognition, Text Classification, Word Embeddings |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/C16-1189/ |
| https://www.aclweb.org/anthology/C16-1189 | |
| PWC | https://paperswithcode.com/paper/dialogue-act-classification-in-domain |
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Morphotactics as Tier-Based Strictly Local Dependencies
| Title | Morphotactics as Tier-Based Strictly Local Dependencies |
| Authors | Al{"e}na Aks{"e}nova, Thomas Graf, Sedigheh Moradi |
| Abstract | |
| Tasks | |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/W16-2019/ |
| https://www.aclweb.org/anthology/W16-2019 | |
| PWC | https://paperswithcode.com/paper/morphotactics-as-tier-based-strictly-local |
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Curation of Dutch Regional Dictionaries
| Title | Curation of Dutch Regional Dictionaries |
| Authors | Henk van den Heuvel, S, Eric ers, Nicoline van der Sijs |
| Abstract | This paper describes the process of semi-automatically converting dictionaries from paper to structured text (database) and the integration of these into the CLARIN infrastructure in order to make the dictionaries accessible and retrievable for the research community. The case study at hand is that of the curation of 42 fascicles of the Dictionaries of the Brabantic and Limburgian dialects, and 6 fascicles of the Dictionary of dialects in Gelderland. |
| Tasks | |
| Published | 2016-05-01 |
| URL | https://www.aclweb.org/anthology/L16-1517/ |
| https://www.aclweb.org/anthology/L16-1517 | |
| PWC | https://paperswithcode.com/paper/curation-of-dutch-regional-dictionaries |
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Dictionary-based Domain Adaptation of MT Systems without Retraining
| Title | Dictionary-based Domain Adaptation of MT Systems without Retraining |
| Authors | Rudolf Rosa, Roman Sudarikov, Michal Nov{'a}k, Martin Popel, Ond{\v{r}}ej Bojar |
| Abstract | |
| Tasks | Domain Adaptation, Machine Translation |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/W16-2334/ |
| https://www.aclweb.org/anthology/W16-2334 | |
| PWC | https://paperswithcode.com/paper/dictionary-based-domain-adaptation-of-mt |
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English-Portuguese Biomedical Translation Task Using a Genuine Phrase-Based Statistical Machine Translation Approach
| Title | English-Portuguese Biomedical Translation Task Using a Genuine Phrase-Based Statistical Machine Translation Approach |
| Authors | Jos{'e} Aires, Gabriel Lopes, Lu{'\i}s Gomes |
| Abstract | |
| Tasks | Language Modelling, Machine Translation |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/W16-2335/ |
| https://www.aclweb.org/anthology/W16-2335 | |
| PWC | https://paperswithcode.com/paper/english-portuguese-biomedical-translation |
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| Framework | |
DTED: Evaluation of Machine Translation Structure Using Dependency Parsing and Tree Edit Distance
| Title | DTED: Evaluation of Machine Translation Structure Using Dependency Parsing and Tree Edit Distance |
| Authors | Martin McCaffery, Mark-Jan Nederhof |
| Abstract | |
| Tasks | Dependency Parsing, Machine Translation |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/W16-2340/ |
| https://www.aclweb.org/anthology/W16-2340 | |
| PWC | https://paperswithcode.com/paper/dted-evaluation-of-machine-translation |
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| Framework | |
Findings of the WMT 2016 Bilingual Document Alignment Shared Task
| Title | Findings of the WMT 2016 Bilingual Document Alignment Shared Task |
| Authors | Christian Buck, Philipp Koehn |
| Abstract | |
| Tasks | Machine Translation |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/W16-2347/ |
| https://www.aclweb.org/anthology/W16-2347 | |
| PWC | https://paperswithcode.com/paper/findings-of-the-wmt-2016-bilingual-document |
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CharacTer: Translation Edit Rate on Character Level
| Title | CharacTer: Translation Edit Rate on Character Level |
| Authors | Weiyue Wang, Jan-Thorsten Peter, Hendrik Rosendahl, Hermann Ney |
| Abstract | |
| Tasks | Machine Translation |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/W16-2342/ |
| https://www.aclweb.org/anthology/W16-2342 | |
| PWC | https://paperswithcode.com/paper/character-translation-edit-rate-on-character |
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Continuous Expressive Speaking Styles Synthesis based on CVSM and MR-HMM
| Title | Continuous Expressive Speaking Styles Synthesis based on CVSM and MR-HMM |
| Authors | Jaime Lorenzo-Trueba, Roberto Barra-Chicote, Ascension Gallardo-Antolin, Junichi Yamagishi, Juan M. Montero |
| Abstract | This paper introduces a continuous system capable of automatically producing the most adequate speaking style to synthesize a desired target text. This is done thanks to a joint modeling of the acoustic and lexical parameters of the speaker models by adapting the CVSM projection of the training texts using MR-HMM techniques. As such, we consider that as long as sufficient variety in the training data is available, we should be able to model a continuous lexical space into a continuous acoustic space. The proposed continuous automatic text to speech system was evaluated by means of a perceptual evaluation in order to compare them with traditional approaches to the task. The system proved to be capable of conveying the correct expressiveness (average adequacy of 3.6) with an expressive strength comparable to oracle traditional expressive speech synthesis (average of 3.6) although with a drop in speech quality mainly due to the semi-continuous nature of the data (average quality of 2.9). This means that the proposed system is capable of improving traditional neutral systems without requiring any additional user interaction. |
| Tasks | Speech Recognition, Speech Synthesis |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/C16-1036/ |
| https://www.aclweb.org/anthology/C16-1036 | |
| PWC | https://paperswithcode.com/paper/continuous-expressive-speaking-styles |
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Creating a General Russian Sentiment Lexicon
| Title | Creating a General Russian Sentiment Lexicon |
| Authors | Natalia Loukachevitch, Anatolii Levchik |
| Abstract | The paper describes the new Russian sentiment lexicon - RuSentiLex. The lexicon was gathered from several sources: opinionated words from domain-oriented Russian sentiment vocabularies, slang and curse words extracted from Twitter, objective words with positive or negative connotations from a news collection. The words in the lexicon having different sentiment orientations in specific senses are linked to appropriate concepts of the thesaurus of Russian language RuThes. All lexicon entries are classified according to four sentiment categories and three sources of sentiment (opinion, emotion, or fact). The lexicon can serve as the first version for the construction of domain-specific sentiment lexicons or can be used for feature generation in machine-learning approaches. In this role, the RuSentiLex lexicon was utilized by the participants of the SentiRuEval-2016 Twitter reputation monitoring shared task and allowed them to achieve high results. |
| Tasks | |
| Published | 2016-05-01 |
| URL | https://www.aclweb.org/anthology/L16-1186/ |
| https://www.aclweb.org/anthology/L16-1186 | |
| PWC | https://paperswithcode.com/paper/creating-a-general-russian-sentiment-lexicon |
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Joint Line Segmentation and Transcription for End-to-End Handwritten Paragraph Recognition
| Title | Joint Line Segmentation and Transcription for End-to-End Handwritten Paragraph Recognition |
| Authors | Theodore Bluche |
| Abstract | Offline handwriting recognition systems require cropped text line images for both training and recognition. On the one hand, the annotation of position and transcript at line level is costly to obtain. On the other hand, automatic line segmentation algorithms are prone to errors, compromising the subsequent recognition. In this paper, we propose a modification of the popular and efficient Multi-Dimensional Long Short-Term Memory Recurrent Neural Networks (MDLSTM-RNNs) to enable end-to-end processing of handwritten paragraphs. More particularly, we replace the collapse layer transforming the two-dimensional representation into a sequence of predictions by a recurrent version which can select one line at a time. In the proposed model, a neural network performs a kind of implicit line segmentation by computing attention weights on the image representation. The experiments on paragraphs of Rimes and IAM databases yield results that are competitive with those of networks trained at line level, and constitute a significant step towards end-to-end transcription of full documents. |
| Tasks | |
| Published | 2016-12-01 |
| URL | http://papers.nips.cc/paper/6257-joint-line-segmentation-and-transcription-for-end-to-end-handwritten-paragraph-recognition |
| http://papers.nips.cc/paper/6257-joint-line-segmentation-and-transcription-for-end-to-end-handwritten-paragraph-recognition.pdf | |
| PWC | https://paperswithcode.com/paper/joint-line-segmentation-and-transcription-for-1 |
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