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| 61 |
Big Five vs. Prosodic Features as Cues to Detect Abnormality in SSPNET-Personality Corpus
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In: Interspeech ; https://hal.inria.fr/hal-01583510 ; Interspeech, Aug 2017, Stockholm, Sweden ; http://www.interspeech2017.org/ (2017)
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| 62 |
Emergent Jaw Predominance in Vocal Development through Stochastic Optimization
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In: ISSN: 2379-8920 ; EISSN: 2379-8939 ; IEEE Transactions on Cognitive and Developmental Systems ; https://hal.inria.fr/hal-01578075 ; IEEE Transactions on Cognitive and Developmental Systems, Institute of Electrical and Electronics Engineers, Inc, 2017, pp.1-12. ⟨10.1109/TCDS.2017.2704912⟩ ; http://ieeexplore.ieee.org/document/7955101/ (2017)
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| 63 |
Database and Expert Systems Applications - 28th International Conference, DEXA 2017, Lyon, France, Proceedings part II
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In: ISSN: 0302-9743 ; Lecture Notes in Computer Science ; 28th International Conference on Database and Expert Systems Applications and Workshops (DEXA 2017) ; https://hal.archives-ouvertes.fr/hal-03120290 ; Benslimane, Djamal; Damiani, Ernesto; Grosky, William I.; Hameurlain, Abdelkader; Sheth, Amit P.; Wagner, Roland R. 28th International Conference on Database and Expert Systems Applications and Workshops (DEXA 2017), Aug 2017, Lyon, France. Lecture Notes in Computer Science, 10439 (Part II), Springer, 2017, Database and Expert Systems Applications 28th International Conference, DEXA 2017, Lyon, France, 978-3-319-64470-7. ⟨10.1007/978-3-319-64471-4⟩ ; https://link.springer.com/book/10.1007%2F978-3-319-64471-4 (2017)
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| 64 |
Database and Expert Systems Applications - 28th International Conference, DEXA 2017, Lyon, France, Proceedings part I
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In: ISSN: 0302-9743 ; Lecture Notes in Computer Science ; 28th International Conference on Database and Expert Systems Applications and Workshops (DEXA 2017) ; https://hal.archives-ouvertes.fr/hal-03120283 ; Benslimane, Djamal; Damiani, Ernesto; Grosky, William I.; Hameurlain, Abdelkader; Amit P., Sheth; Wagner, Roland. 28th International Conference on Database and Expert Systems Applications and Workshops (DEXA 2017), Aug 2017, Lyon, France. Lecture Notes in Computer Science, 10438, Springer, 517 p., 2017, Lecture Notes in Computer Science book series (LNCS), 978-3-319-64467-7 ; https://link.springer.com/book/10.1007%2F978-3-319-64468-4 (2017)
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| 65 |
Deep Learning And Competition In Psycholinguistic Research ...
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| 66 |
Deep Learning And Competition In Psycholinguistic Research ...
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| 67 |
Introducing statistical machine translation in translator training : from uses and perceptions to course design, and back again
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| 68 |
Acoustic sequences in non-human animals : a tutorial review and prospectus
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Kershenbaum, Arik; Blumstein, Dan; Roch, Marie; Akçay, Çaglar; Backus, Gregory; Bee, Mark A.; Bohn, Kirsten; Cao, Yan; Carter, Gerald; Cäsar, Cristiane; Coen, Michael; De Ruiter, Stacy Lynn; Doyle, Laurance; Edelman, Shimon; Ferrer-i-Cancho, Ramon; Freeberg, Todd M.; Garland, Ellen Clare; Gustison, Morgan; Harley, Heidi E.; Huetz, Chloé; Hughes, Melissa; Bruno, Julia Hyland; Ilany, Amiyaal; Jin, Dezhe Z.; Johnson, Michael; Ju, Chenghui; Karnowski, Jeremy; Lohr, Bernard; Manser, Marta; McCowan, Brenda; Mercado III, Eduardo; Narins, Peter M.; Piel, Alex; Rice, Megan; Salmi, Roberta; Sasahara, Kazutoshi; Sayigh, Laela; Shiu, Yu; Taylor, Charles; Vallejo, Edgar E.; Waller, Sara; Zamora-Gutierrez, Veronica. - 2017
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Abstract:
Animal acoustic communication often takes the form of complex sequences, made up of multiple distinct acoustic units. Apart from the well-known example of birdsong, other animals such as insects, amphibians,and mammals (including bats, rodents, primates, and cetaceans) also generate complex acoustic sequences. Occasionally, such as with birdsong, the adaptive role of these sequences seems clear (e.g. mate attraction and territorial defence). More often however, researchers have only begun to characterise – let alone understand – the significance and meaning of acoustic sequences. Hypotheses abound, but there is little agreement as to how sequences should be defined and analysed. Our review aims to outline suitable methods for testing these hypotheses, and to describe the major limitations to our current and near-future knowledge on questions of acoustic sequences. This review and prospectus is the result of a collaborative effort between 43 scientists from the fields of animal behaviour, ecology and evolution, signal processing, machine learning,quantitative linguistics, and information theory, who gathered for a 2013 workshop entitled, ‘Analysing vocal sequences in animals’. Our goal is to present not just a review of the state of the art, but to propose a methodological framework that summarises what we suggest are the best practices for research in this field,across taxa and across disciplines. We also provide a tutorial-style introduction to some of the most promising algorithmic approaches for analysing sequences. We divide our review into three sections: identifying the distinct units of an acoustic sequence, describing the different ways that information can be contained within a sequence, and analysing the structure of that sequence. Each of these sections is further subdivided to address the key questions and approaches in that area. We propose a uniform, systematic, and comprehensive approach to studying sequences, with the goal of clarifying research terms used in different fields, and facilitating collaboration and comparative studies. Allowing greater interdisciplinary collaboration will facilitate the investigation of many important questions in the evolution of communication and sociality. ; Postprint ; Peer reviewed
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Keyword:
Acoustic communication; Information; Information theory; Machine learning; Markov model; Meaning; Network analysis; QA; QA Mathematics; QH301; QH301 Biology; T-NDAS; Vocalisation
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URL: http://hdl.handle.net/10023/7848
https://doi.org/10.1111/brv.12160
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| 69 |
Learning from Noisy Data in Statistical Machine Translation
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| 70 |
Log-Linear Weight Optimization Using Discriminative Ridge Regression Method in Statistical Machine Translation
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| 71 |
A new language model based on possibility theory
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In: Springer LNCS series, Lecture Notes in Computer Science. ; https://hal.inria.fr/hal-01336535 ; Springer LNCS series, Lecture Notes in Computer Science., 2016 (2016)
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| 72 |
Adaptation au locuteur pour la séparation de la parole par NMF
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In: https://hal.sorbonne-universite.fr/hal-01482183 ; [Stage] STMS - Sciences et Technologies de la Musique et du Son UMR 9912 IRCAM-CNRS-UPMC. 2016 (2016)
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| 73 |
Coreference Resolution for French Oral Data: Machine Learning Experiments with ANCOR
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In: 17th International Conference on Intelligent Text Processing and Computational Linguistics (CICLing'2016) ; https://hal.archives-ouvertes.fr/hal-01344977 ; 17th International Conference on Intelligent Text Processing and Computational Linguistics (CICLing'2016), Apr 2016, Konya, Turkey ; http://www.cicling.org/2016/ (2016)
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| 74 |
Phrase-Based Language Model in Statistical Machine Translation
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In: ISSN: 0976-0962 ; International Journal of Computational Linguistics and Applications ; https://hal.inria.fr/hal-01336485 ; International Journal of Computational Linguistics and Applications, Alexander Gelbukh, 2016 (2016)
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| 75 |
Acoustic Sequences in Non-human Animals: A Tutorial Review and Prospectus
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In: Electrical and Computer Engineering Faculty Research and Publications (2016)
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| 76 |
Investigation of Back-off Based Interpolation Between Recurrent Neural Network and N-gram Language Models (Author's Manuscript)
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| 78 |
Acoustic sequences in nonâ human animals: a tutorial review and prospectus
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| 79 |
Phrase-based statistical machine translation: explanation of its processes and statistical models and evaluation of the English to Spanish translations produced
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| 80 |
A Data-driven bayesian approach to automatic rhythm analysis of indian art music
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In: TDX (Tesis Doctorals en Xarxa) (2016)
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