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Integration of Dubbing Constraints into Machine Translation
<span title="">2019</span>
<i title="Association for Computational Linguistics">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ofil6chs6zhkndqe6tcritiiwm" style="color: black;">Proceedings of the Fourth Conference on Machine Translation (Volume 1: Research Papers)</a>
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Translation systems aim to perform a meaningpreserving conversion of linguistic material (typically text but also speech) from a source to a target language (and, to a lesser degree, the corresponding socio-cultural contexts). Dubbing, i. e., the lip-synchronous translation and revoicing of speech adds to this constraints about the close matching of phonetic and resulting visemic synchrony characteristics of source and target material. There is an inherent conflict between a translation's
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... g preservation and its 'dubbability' and the resulting trade-off can be controlled by weighing the synchrony constraints. We introduce our work, which to the best of our knowledge is the first of its kind, on integrating synchrony constraints into the machine translation paradigm. We present first results for the integration of synchrony constraints into encoder decoder-based neural machine translation and show that considerably more 'dubbable' translations can be achieved with only a small impact on BLEU score, and dubbability improves more steeply than BLEU degrades.
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SymPy: symbolic computing in Python
<span title="2017-01-02">2017</span>
<i title="PeerJ">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/zs2czkfyybggbpvr26rbyxpsjy" style="color: black;">PeerJ Computer Science</a>
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SymPy is an open source computer algebra system written in pure Python. It is built with a focus on extensibility and ease of use, through both interactive and programmatic applications. These characteristics have led SymPy to become a popular symbolic library for the scientific Python ecosystem. This paper presents the architecture of SymPy, a description of its features, and a discussion of select submodules. The supplementary material provide additional examples and further outline details of the architecture and features of SymPy.
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AIMpy: A Python code to solve Schrodinger-like equations with the Asymptotic Iteration Method
<span title="2020-10-06">2020</span>
<i title="World Scientific Pub Co Pte Lt">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/hbx4gtuktje5xlucfjsfimesou" style="color: black;">International Journal of Modern Physics C</a>
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<span title="2021-12-06">2021</span> <span class="release-stage" >pre-print</span> <span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2112.02934v1">arXiv:2112.02934v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/bs6t5gy2hnbidjxsgdpjd6jolu">fatcat:bs6t5gy2hnbidjxsgdpjd6jolu</a> </span>
Terrel, Štěpán Roučka, Ashutosh Saboo, Isuru Fernando, Sumith
Kulal, Robert Cimrman, and Anthony Scopatz. Sympy: symbolic computing in python. ...
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Learning advanced mathematical computations from examples
[article]
<span title="2021-03-19">2021</span>
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arXiv
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<span title="2020-06-11">2020</span>
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Štěpán Roučka, Ashutosh Saboo, Isuru Fernando, Sumith Kulal, Robert Cimrman, and Anthony Scopatz. Sympy: symbolic computing in python. PeerJ Computer Science, 3:e103, January 2017. ...
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Matrix decompositions over the double numbers
[article]
<span title="2021-12-06">2021</span>
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<span title="2021-05-17">2021</span>
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Terrel,
Štěpán Roučka, Ashutosh Saboo, Isuru Fernando, Sumith Kulal, Robert
Cimrman, and Anthony Scopatz. Sympy: symbolic computing in python. ...
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Unit commitment considering multiple charging and discharging scenarios of plug-in electric vehicles
<span title="">2015</span>
<i title="IEEE">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/qm5nunzmyva4tfjekdcm34uvhq" style="color: black;">2015 International Joint Conference on Neural Networks (IJCNN)</a>
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HMAX Model: A Survey [#15576]
Chang Liu and Fuchun Sun
P383 Composer Classification based on Temporal Coding in Adaptive Spiking Neural Networks [#15765]
Chaitanya Prasad Narisetty, Krishnakant Saboo ...
processing
Tuesday, July 14, 4:40PM-6:20PM, Room: Park Suite, Chair: Hagiwara, Masafumi
4:40PM A Cascade of Linguistic CMAC Neural Networks for Decision Making [#15198]
Hongmei He, Zhenhuan Zhu, Ashutosh ...
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