Literatura académica sobre el tema "Speech prediction EEG"
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Artículos de revistas sobre el tema "Speech prediction EEG"
Maki, Hayato, Sakriani Sakti, Hiroki Tanaka y Satoshi Nakamura. "Quality prediction of synthesized speech based on tensor structured EEG signals". PLOS ONE 13, n.º 6 (14 de junio de 2018): e0193521. http://dx.doi.org/10.1371/journal.pone.0193521.
Texto completoGibson, Jerry. "Entropy Power, Autoregressive Models, and Mutual Information". Entropy 20, n.º 10 (30 de septiembre de 2018): 750. http://dx.doi.org/10.3390/e20100750.
Texto completoSohoglu, Ediz y Matthew H. Davis. "Perceptual learning of degraded speech by minimizing prediction error". Proceedings of the National Academy of Sciences 113, n.º 12 (8 de marzo de 2016): E1747—E1756. http://dx.doi.org/10.1073/pnas.1523266113.
Texto completoShen, Stanley, Jess R. Kerlin, Heather Bortfeld y Antoine J. Shahin. "The Cross-Modal Suppressive Role of Visual Context on Speech Intelligibility: An ERP Study". Brain Sciences 10, n.º 11 (2 de noviembre de 2020): 810. http://dx.doi.org/10.3390/brainsci10110810.
Texto completoSriraam, N. "EEG Based Thought Translator". International Journal of Biomedical and Clinical Engineering 2, n.º 1 (enero de 2013): 50–62. http://dx.doi.org/10.4018/ijbce.2013010105.
Texto completoWeissbart, Hugo, Katerina D. Kandylaki y Tobias Reichenbach. "Cortical Tracking of Surprisal during Continuous Speech Comprehension". Journal of Cognitive Neuroscience 32, n.º 1 (enero de 2020): 155–66. http://dx.doi.org/10.1162/jocn_a_01467.
Texto completoMacGregor, Lucy J., Jennifer M. Rodd, Rebecca A. Gilbert, Olaf Hauk, Ediz Sohoglu y Matthew H. Davis. "The Neural Time Course of Semantic Ambiguity Resolution in Speech Comprehension". Journal of Cognitive Neuroscience 32, n.º 3 (marzo de 2020): 403–25. http://dx.doi.org/10.1162/jocn_a_01493.
Texto completoMoinuddin, Kazi Ashraf, Felix Havugimana, Rakib Al-Fahad, Gavin M. Bidelman y Mohammed Yeasin. "Unraveling Spatial-Spectral Dynamics of Speech Categorization Speed Using Convolutional Neural Networks". Brain Sciences 13, n.º 1 (30 de diciembre de 2022): 75. http://dx.doi.org/10.3390/brainsci13010075.
Texto completoCimtay, Yucel y Erhan Ekmekcioglu. "Investigating the Use of Pretrained Convolutional Neural Network on Cross-Subject and Cross-Dataset EEG Emotion Recognition". Sensors 20, n.º 7 (4 de abril de 2020): 2034. http://dx.doi.org/10.3390/s20072034.
Texto completoStrauß, Antje, Sonja A. Kotz y Jonas Obleser. "Narrowed Expectancies under Degraded Speech: Revisiting the N400". Journal of Cognitive Neuroscience 25, n.º 8 (agosto de 2013): 1383–95. http://dx.doi.org/10.1162/jocn_a_00389.
Texto completoTesis sobre el tema "Speech prediction EEG"
Cheimariou, Spyridoula. "Prediction in aging language processing". Diss., University of Iowa, 2016. https://ir.uiowa.edu/etd/3056.
Texto completoRichieri, Raphaëlle. "Substrats neuro-fonctionnels de la stimulation magnétique transcrânienne répétitive dans la dépression pharmaco-résistante". Thesis, Aix-Marseille, 2014. http://www.theses.fr/2014AIXM5026.
Texto completoTreatment-resistance is a common outcome of a major depressive episode. Repetitive transcranial magnetic stimulation has been put forward as a new technique to treat this debilitating illness. The first objective of our thesis was to characterize the functional substrates of treatment-resistant depression (TRD) using SPECT technique, in order to identify specific patterns of brain abnormalities. In a second part, based on existing work on the antidepressant mechanisms of rTMS, we investigated the predictive value of two neurofunctional biomarkers: SPECT and EEG. Finally, we studied brain SPECT perfusion changes underlying therapeutic efficiency and improvement of quality of life, as currently recommended. Our results showed the existence of a common pattern of brain perfusion in treatment-resistant patients involving the fronto-temporal regions and the cerebellum, regardless the type of depression. At baseline, SPECT brain perfusion and alpha EEG band power could predict individual clinical improvement in TRD-patients treated with rTMS. Regardless the stimulated side, the antidepressant efficacy of rTMS consisted in similar changes in cerebral perfusion. Finally, our results have identified distinct dysfunctional brain regions and confirm the interest of a complementary approach to depression, by assessing quality of life
Capítulos de libros sobre el tema "Speech prediction EEG"
Di Napoli, Claudia, Alessandro Messeri, Martin Novák, João Rio, Joanna Wieczorek, Marco Morabito, Pedro Silva, Alfonso Crisci y Florian Pappenberger. "The Universal Thermal Climate Index as an Operational Forecasting Tool of Human Biometeorological Conditions in Europe". En Applications of the Universal Thermal Climate Index UTCI in Biometeorology, 193–208. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-76716-7_10.
Texto completoChavan, Puja A. y Sharmishta Desai. "A Review on BCI Emotions Classification for EEG Signals Using Deep Learning". En Recent Trends in Intensive Computing. IOS Press, 2021. http://dx.doi.org/10.3233/apc210241.
Texto completo"Tools for Bypassing Basic Language and Speech Deficits". En Advances in Early Childhood and K-12 Education, 197–231. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-7998-9442-1.ch008.
Texto completoRamasamy, Prema, Shri Tharanyaa Jothimani Palanivelu y Abin Sathesan. "Certain Applications of LabVIEW in the Field of Electronics and Communication". En LabVIEW - A Flexible Environment for Modeling and Daily Laboratory Use. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.96301.
Texto completoHu, Weifei. "Artificial Intelligence in Wind Energy". En Wind Energy Applications, 6–181. ASME, 2022. http://dx.doi.org/10.1115/1.885727_ch6.
Texto completoBäck, Thomas. "Artificial Landscapes". En Evolutionary Algorithms in Theory and Practice. Oxford University Press, 1996. http://dx.doi.org/10.1093/oso/9780195099713.003.0008.
Texto completoWeich, Scott y Martin Prince. "Cohort studies". En Practical Psychiatric Epidemiology, 155–76. Oxford University Press, 2003. http://dx.doi.org/10.1093/med/9780198515517.003.0009.
Texto completoActas de conferencias sobre el tema "Speech prediction EEG"
Sakthi, Madhumitha, Ahmed Tewfik y Bharath Chandrasekaran. "Native Language and Stimuli Signal Prediction from EEG". En ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2019. http://dx.doi.org/10.1109/icassp.2019.8682563.
Texto completoWilliamson, James R., Daniel W. Bliss y David W. Browne. "Epileptic seizure prediction using the spatiotemporal correlation structure of intracranial EEG". En ICASSP 2011 - 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2011. http://dx.doi.org/10.1109/icassp.2011.5946491.
Texto completoMerino, Lenis Mauricio, Jia Meng, Stephen Gordon, Brent J. Lance, Tony Johnson, Victor Paul, Kay Robbins, Jean M. Vettel y Yufei Huang. "A bag-of-words model for task-load prediction from EEG in complex environments". En ICASSP 2013 - 2013 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2013. http://dx.doi.org/10.1109/icassp.2013.6637846.
Texto completoPark, Yun, Theoden Netoff y Keshab Parhi. "Seizure prediction with spectral power of time/space-differential EEG signals using cost-sensitive support vector machine". En 2010 IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE, 2010. http://dx.doi.org/10.1109/icassp.2010.5494922.
Texto completoMa, Chao, F. A. Rezaur Rahman Chowdhury, Aryan Deshwal, Md Rakibul Islam, Janardhan Rao Doppa y Dan Roth. "Randomized Greedy Search for Structured Prediction: Amortized Inference and Learning". En Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/713.
Texto completoYang, Chaoqi, Cao Xiao, Lucas Glass y Jimeng Sun. "Change Matters: Medication Change Prediction with Recurrent Residual Networks". En Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/513.
Texto completoLiu, Jinlong, Christopher Ulishney y Cosmin E. Dumitrescu. "Application of Random Forest Machine Learning Models to Forecast Combustion Profile Parameters of a Natural Gas Spark Ignition Engine". En ASME 2020 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/imece2020-23973.
Texto completoShao, Yunli y Zongxuan Sun. "Optimal Speed Control for a Connected and Autonomous Electric Vehicle Considering Battery Aging and Regenerative Braking Limits". En ASME 2019 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/dscc2019-9075.
Texto completoHuang, Rongjie, Max W. Y. Lam, Jun Wang, Dan Su, Dong Yu, Yi Ren y Zhou Zhao. "FastDiff: A Fast Conditional Diffusion Model for High-Quality Speech Synthesis". En Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/577.
Texto completoWang, Feng, Mauro Carnevale, Luca di Mare y Simon Gallimore. "Simulation of Multi-Stage Compressor at Off-Design Conditions". En ASME Turbo Expo 2017: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/gt2017-64964.
Texto completoInformes sobre el tema "Speech prediction EEG"
Michaels, Michelle, Theodore Letcher, Sandra LeGrand, Nicholas Webb y Justin Putnam. Implementation of an albedo-based drag partition into the WRF-Chem v4.1 AFWA dust emission module. Engineer Research and Development Center (U.S.), enero de 2021. http://dx.doi.org/10.21079/11681/42782.
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