Paper Group NANR 3
A Database of Laryngeal High-Speed Videos with Simultaneous High-Quality Audio Recordings of Pathological and Non-Pathological Voices. OpenDial: A Toolkit for Developing Spoken Dialogue Systems with Probabilistic Rules. Selective inference for group-sparse linear models. Special Session - The Future Directions of Dialogue-Based Intelligent Personal …
A Database of Laryngeal High-Speed Videos with Simultaneous High-Quality Audio Recordings of Pathological and Non-Pathological Voices
| Title | A Database of Laryngeal High-Speed Videos with Simultaneous High-Quality Audio Recordings of Pathological and Non-Pathological Voices |
| Authors | Philipp Aichinger, Immer Roesner, Matthias Leonhard, Doris-Maria Denk-Linnert, Wolfgang Bigenzahn, Berit Schneider-Stickler |
| Abstract | Auditory voice quality judgements are used intensively for the clinical assessment of pathological voice. Voice quality concepts are fuzzily defined and poorly standardized however, which hinders scientific and clinical communication. The described database documents a wide variety of pathologies and is used to investigate auditory voice quality concepts with regard to phonation mechanisms. The database contains 375 laryngeal high-speed videos and simultaneous high-quality audio recordings of sustained phonations of 80 pathological and 40 non-pathological subjects. Interval wise annotations regarding video and audio quality, as well as voice quality ratings are provided. Video quality is annotated for the visibility of anatomical structures and artefacts such as blurring or reduced contrast. Voice quality annotations include ratings on the presence of dysphonia and diplophonia. The purpose of the database is to aid the formulation of observationally well-founded models of phonation and the development of model-based automatic detectors for distinct types of phonation, especially for clinically relevant nonmodal voice phenomena. Another application is the training of audio-based fundamental frequency extractors on video-based reference fundamental frequencies. |
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| Published | 2016-05-01 |
| URL | https://www.aclweb.org/anthology/L16-1122/ |
| https://www.aclweb.org/anthology/L16-1122 | |
| PWC | https://paperswithcode.com/paper/a-database-of-laryngeal-high-speed-videos |
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OpenDial: A Toolkit for Developing Spoken Dialogue Systems with Probabilistic Rules
| Title | OpenDial: A Toolkit for Developing Spoken Dialogue Systems with Probabilistic Rules |
| Authors | Pierre Lison, Casey Kennington |
| Abstract | |
| Tasks | Dialogue Management, Speech Recognition, Speech Synthesis, Spoken Dialogue Systems |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/P16-4012/ |
| https://www.aclweb.org/anthology/P16-4012 | |
| PWC | https://paperswithcode.com/paper/opendial-a-toolkit-for-developing-spoken |
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Selective inference for group-sparse linear models
| Title | Selective inference for group-sparse linear models |
| Authors | Fan Yang, Rina Foygel Barber, Prateek Jain, John Lafferty |
| Abstract | We develop tools for selective inference in the setting of group sparsity, including the construction of confidence intervals and p-values for testing selected groups of variables. Our main technical result gives the precise distribution of the magnitude of the projection of the data onto a given subspace, and enables us to develop inference procedures for a broad class of group-sparse selection methods, including the group lasso, iterative hard thresholding, and forward stepwise regression. We give numerical results to illustrate these tools on simulated data and on health record data. |
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| Published | 2016-12-01 |
| URL | http://papers.nips.cc/paper/6437-selective-inference-for-group-sparse-linear-models |
| http://papers.nips.cc/paper/6437-selective-inference-for-group-sparse-linear-models.pdf | |
| PWC | https://paperswithcode.com/paper/selective-inference-for-group-sparse-linear |
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Special Session - The Future Directions of Dialogue-Based Intelligent Personal Assistants
| Title | Special Session - The Future Directions of Dialogue-Based Intelligent Personal Assistants |
| Authors | Yoichi Matsuyama, Alex Papangelis, ros |
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| Published | 2016-09-01 |
| URL | https://www.aclweb.org/anthology/W16-3606/ |
| https://www.aclweb.org/anthology/W16-3606 | |
| PWC | https://paperswithcode.com/paper/special-session-the-future-directions-of |
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Providing and Analyzing NLP Terms for our Community
| Title | Providing and Analyzing NLP Terms for our Community |
| Authors | Gil Francopoulo, Joseph Mariani, Patrick Paroubek, Fr{'e}d{'e}ric Vernier |
| Abstract | By its own nature, the Natural Language Processing (NLP) community is a priori the best equipped to study the evolution of its own publications, but works in this direction are rare and only recently have we seen a few attempts at charting the field. In this paper, we use the algorithms, resources, standards, tools and common practices of the NLP field to build a list of terms characteristic of ongoing research, by mining a large corpus of scientific publications, aiming at the largest possible exhaustivity and covering the largest possible time span. Study of the evolution of this term list through time reveals interesting insights on the dynamics of field and the availability of the term database and of the corpus (for a large part) make possible many further comparative studies in addition to providing a test field for a new graphic interface designed to perform visual time analytics of large sized thesauri. |
| Tasks | Named Entity Recognition, Optical Character Recognition |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/W16-4711/ |
| https://www.aclweb.org/anthology/W16-4711 | |
| PWC | https://paperswithcode.com/paper/providing-and-analyzing-nlp-terms-for-our |
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Combining Translation Memories and Syntax-Based SMT: Experiments with Real Industrial Data
| Title | Combining Translation Memories and Syntax-Based SMT: Experiments with Real Industrial Data |
| Authors | Liangyou Li, Carla Parra Escartin, Qun Liu |
| Abstract | |
| Tasks | Machine Translation |
| Published | 2016-01-01 |
| URL | https://www.aclweb.org/anthology/W16-3406/ |
| https://www.aclweb.org/anthology/W16-3406 | |
| PWC | https://paperswithcode.com/paper/combining-translation-memories-and-syntax |
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Proceedings of the Workshop on Discontinuous Structures in Natural Language Processing
| Title | Proceedings of the Workshop on Discontinuous Structures in Natural Language Processing |
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| Published | 2016-06-01 |
| URL | https://www.aclweb.org/anthology/W16-0900/ |
| https://www.aclweb.org/anthology/W16-0900 | |
| PWC | https://paperswithcode.com/paper/proceedings-of-the-workshop-on-discontinuous |
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Czech Legal Text Treebank 1.0
| Title | Czech Legal Text Treebank 1.0 |
| Authors | Vincent Kr{'\i}{\v{z}}, Barbora Hladk{'a}, Zde{\v{n}}ka Ure{\v{s}}ov{'a} |
| Abstract | We introduce a new member of the family of Prague dependency treebanks. The Czech Legal Text Treebank 1.0 is a morphologically and syntactically annotated corpus of 1,128 sentences. The treebank contains texts from the legal domain, namely the documents from the Collection of Laws of the Czech Republic. Legal texts differ from other domains in several language phenomena influenced by rather high frequency of very long sentences. A manual annotation of such sentences presents a new challenge. We describe a strategy and tools for this task. The resulting treebank can be explored in various ways. It can be downloaded from the LINDAT/CLARIN repository and viewed locally using the TrEd editor or it can be accessed on-line using the KonText and TreeQuery tools. |
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| Published | 2016-05-01 |
| URL | https://www.aclweb.org/anthology/L16-1378/ |
| https://www.aclweb.org/anthology/L16-1378 | |
| PWC | https://paperswithcode.com/paper/czech-legal-text-treebank-10 |
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LSTM Autoencoders for Dialect Analysis
| Title | LSTM Autoencoders for Dialect Analysis |
| Authors | Taraka Rama, {\c{C}}a{\u{g}}r{\i} {\c{C}}{"o}ltekin |
| Abstract | Computational approaches for dialectometry employed Levenshtein distance to compute an aggregate similarity between two dialects belonging to a single language group. In this paper, we apply a sequence-to-sequence autoencoder to learn a deep representation for words that can be used for meaningful comparison across dialects. In contrast to the alignment-based methods, our method does not require explicit alignments. We apply our architectures to three different datasets and show that the learned representations indicate highly similar results with the analyses based on Levenshtein distance and capture the traditional dialectal differences shown by dialectologists. |
| Tasks | Dimensionality Reduction |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/W16-4803/ |
| https://www.aclweb.org/anthology/W16-4803 | |
| PWC | https://paperswithcode.com/paper/lstm-autoencoders-for-dialect-analysis |
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A News Editorial Corpus for Mining Argumentation Strategies
| Title | A News Editorial Corpus for Mining Argumentation Strategies |
| Authors | Khalid Al-Khatib, Henning Wachsmuth, Johannes Kiesel, Matthias Hagen, Benno Stein |
| Abstract | Many argumentative texts, and news editorials in particular, follow a specific strategy to persuade their readers of some opinion or attitude. This includes decisions such as when to tell an anecdote or where to support an assumption with statistics, which is reflected by the composition of different types of argumentative discourse units in a text. While several argument mining corpora have recently been published, they do not allow the study of argumentation strategies due to incomplete or coarse-grained unit annotations. This paper presents a novel corpus with 300 editorials from three diverse news portals that provides the basis for mining argumentation strategies. Each unit in all editorials has been assigned one of six types by three annotators with a high Fleiss{'} Kappa agreement of 0.56. We investigate various challenges of the annotation process and we conduct a first corpus analysis. Our results reveal different strategies across the news portals, exemplifying the benefit of studying editorials{—}a so far underresourced text genre in argument mining. |
| Tasks | Argument Mining |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/C16-1324/ |
| https://www.aclweb.org/anthology/C16-1324 | |
| PWC | https://paperswithcode.com/paper/a-news-editorial-corpus-for-mining |
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BrainBench: A Brain-Image Test Suite for Distributional Semantic Models
| Title | BrainBench: A Brain-Image Test Suite for Distributional Semantic Models |
| Authors | Haoyan Xu, Brian Murphy, Alona Fyshe |
| Abstract | |
| Tasks | |
| Published | 2016-11-01 |
| URL | https://www.aclweb.org/anthology/D16-1213/ |
| https://www.aclweb.org/anthology/D16-1213 | |
| PWC | https://paperswithcode.com/paper/brainbench-a-brain-image-test-suite-for |
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Finding the Middle Ground - A Model for Planning Satisficing Answers
| Title | Finding the Middle Ground - A Model for Planning Satisficing Answers |
| Authors | Sabine Janzen, Wolfgang Maa{\ss}, Tobias Kowatsch |
| Abstract | |
| Tasks | Question Answering |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/P16-1052/ |
| https://www.aclweb.org/anthology/P16-1052 | |
| PWC | https://paperswithcode.com/paper/finding-the-middle-ground-a-model-for |
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Which Coreference Evaluation Metric Do You Trust? A Proposal for a Link-based Entity Aware Metric
| Title | Which Coreference Evaluation Metric Do You Trust? A Proposal for a Link-based Entity Aware Metric |
| Authors | Nafise Sadat Moosavi, Michael Strube |
| Abstract | |
| Tasks | Coreference Resolution |
| Published | 2016-08-01 |
| URL | https://www.aclweb.org/anthology/P16-1060/ |
| https://www.aclweb.org/anthology/P16-1060 | |
| PWC | https://paperswithcode.com/paper/which-coreference-evaluation-metric-do-you |
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SentiSys at SemEval-2016 Task 5: Opinion Target Extraction and Sentiment Polarity Detection
| Title | SentiSys at SemEval-2016 Task 5: Opinion Target Extraction and Sentiment Polarity Detection |
| Authors | Hussam Hamdan |
| Abstract | |
| Tasks | Aspect-Based Sentiment Analysis, Opinion Mining, Sentiment Analysis |
| Published | 2016-06-01 |
| URL | https://www.aclweb.org/anthology/S16-1056/ |
| https://www.aclweb.org/anthology/S16-1056 | |
| PWC | https://paperswithcode.com/paper/sentisys-at-semeval-2016-task-5-opinion |
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Incrementally Learning a Dependency Parser to Support Language Documentation in Field Linguistics
| Title | Incrementally Learning a Dependency Parser to Support Language Documentation in Field Linguistics |
| Authors | Morgan Ulinski, Julia Hirschberg, Owen Rambow |
| Abstract | We present experiments in incrementally learning a dependency parser. The parser will be used in the WordsEye Linguistics Tools (WELT) (Ulinski et al., 2014) which supports field linguists documenting a language{'}s syntax and semantics. Our goal is to make syntactic annotation faster for field linguists. We have created a new parallel corpus of descriptions of spatial relations and motion events, based on pictures and video clips used by field linguists for elicitation of language from native speaker informants. We collected descriptions for each picture and video from native speakers in English, Spanish, German, and Egyptian Arabic. We compare the performance of MSTParser (McDonald et al., 2006) and MaltParser (Nivre et al., 2006) when trained on small amounts of this data. We find that MaltParser achieves the best performance. We also present the results of experiments using the parser to assist with annotation. We find that even when the parser is trained on a single sentence from the corpus, annotation time significantly decreases. |
| Tasks | Dependency Parsing |
| Published | 2016-12-01 |
| URL | https://www.aclweb.org/anthology/C16-1043/ |
| https://www.aclweb.org/anthology/C16-1043 | |
| PWC | https://paperswithcode.com/paper/incrementally-learning-a-dependency-parser-to |
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