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Evaluation of Tacotron Based Synthesizers for Spanish and Basque
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In: Applied Sciences; Volume 12; Issue 3; Pages: 1686 (2022)
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CCG Supertagging as Top-down Tree Generation
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In: Proceedings of the Society for Computation in Linguistics (2021)
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Vowel Harmony Viewed as Error-Correcting Code
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In: Proceedings of the Society for Computation in Linguistics (2021)
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Generating Adversarial Examples for Topic-dependent Argument Classification
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In: COMMA 2020 - 8th International Conference on Computational Models of Argument ; https://hal.archives-ouvertes.fr/hal-02933266 ; COMMA 2020 - 8th International Conference on Computational Models of Argument, Sep 2020, Perugia, Italy (2020)
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Automatic word count estimation from daylong child-centered recordings in various language environments using language-independent syllabification of speech
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Complexity of Stability
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In: Leibniz International Proceedings in Informatics, 181 ; 31st International Symposium on Algorithms and Computation (ISAAC 2020) (2020)
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Abstract:
Graph parameters such as the clique number, the chromatic number, and the independence number are central in many areas, ranging from computer networks to linguistics to computational neuroscience to social networks. In particular, the chromatic number of a graph (i.e., the smallest number of colors needed to color all vertices such that no two adjacent vertices are of the same color) can be applied in solving practical tasks as diverse as pattern matching, scheduling jobs to machines, allocating registers in compiler optimization, and even solving Sudoku puzzles. Typically, however, the underlying graphs are subject to (often minor) changes. To make these applications of graph parameters robust, it is important to know which graphs are stable for them in the sense that adding or deleting single edges or vertices does not change them. We initiate the study of stability of graphs for such parameters in terms of their computational complexity. We show that, for various central graph parameters, the problem of determining whether or not a given graph is stable is complete for Θ₂ᵖ, a well-known complexity class in the second level of the polynomial hierarchy, which is also known as "parallel access to NP." ; ISSN:1868-8969
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Keyword:
Clique; coDP; Colorability; Complexity; Criticality; DP; Independent Set; Local Modifications; Parallel Access to NP; Robustness; Satisfiability; Stability; Unfrozenness; Vertex Cover
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URL: https://doi.org/10.3929/ethz-b-000465020 https://hdl.handle.net/20.500.11850/465020
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NAT: Noise-Aware Training for Robust Neural Sequence Labeling
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In: Fraunhofer IAIS (2020)
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VoiceHome-2, an extended corpus for multichannel speech processing in real homes
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In: ISSN: 0167-6393 ; EISSN: 1872-7182 ; Speech Communication ; https://hal.inria.fr/hal-01923108 ; Speech Communication, Elsevier : North-Holland, 2019, 106, pp.68-78. ⟨10.1016/j.specom.2018.11.002⟩ (2019)
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Towards Interpretability and Robustness of Machine Learning Models
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Chen, Jianbo. - : eScholarship, University of California, 2019
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Assessing the Robustness of Conversational Agents using Paraphrases
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Robust speech recognition for german and dialectal broadcast programmes
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In: Fraunhofer IAIS (2018)
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Learning Spatial-Semantic Context with Fully Convolutional Recurrent Network for Online Handwritten Chinese Text Recognition
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Lightweight Spoken Utterance Classification with CFG, tf-idf and Dynamic Programming
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In: ISBN: 978-3-319-68455-0 ; Statistical Language and Speech Processing (SLSP) pp. 143-154 (2017)
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A French corpus for distant-microphone speech processing in real homes
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In: Interspeech 2016 ; https://hal.inria.fr/hal-01343060 ; Interspeech 2016, Sep 2016, San Francisco, United States (2016)
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Reconnaissance automatique de gestes manuels en langue des signes
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In: RFIA 2016 ; RFIA'16: Le vingtième congrès national sur la Reconnaissance des Formes et l'Intelligence Artificielle ; https://hal.archives-ouvertes.fr/hal-01332141 ; RFIA'16: Le vingtième congrès national sur la Reconnaissance des Formes et l'Intelligence Artificielle , Jun 2016, Clermont-Ferrand, France (2016)
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Investigation of Back-off Based Interpolation Between Recurrent Neural Network and N-gram Language Models (Author's Manuscript)
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Lexicographic α-robustness: an application to the 1-median problem
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