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Automatic estimation of parkinson's disease severity from diverse speech tasks.

J. Kim, M. Nasir, R. Gupta, M. Segbroeck, D. Bone, M. Black, Z. Skordilis, Z. Yang, P. Georgiou, and S. Narayanan. INTERSPEECH, page 914-918. ISCA, (2015)

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Univ. -Prof. Dr. Joris van Slageren University of Stuttgart

Electrocatalytic proton reduction: Metal based fused diporphyrins with proton relays for efficient catalysisA. Singha Hazari, S. Chandra, Q. Song, D. Hunger, N. Neuman, J. Slageren, E. Klemm, B. Sarkar, and S. Kar. Dataset, (2024)Related to: Chandra, S., Singha Hazari, A., Song, Q., Hunger, D., Neuman, N. I., van Slageren, J., Klemm, E. & Sarkar, B. (2023). Remarkable Enhancement of Catalytic Activity of Cu-Complexes in the Electrochemical Hydrogen Evolution Reaction by Using Triply Fused Porphyrin. ChemSusChem 16, e202201146. doi: 10.1002/cssc.202201146.

Nina van den Daele University of Stuttgart

Dr. phil. Leo van Waveren University of Stuttgart

Dr. Thijs van Westen University of Stuttgart

Jan Vanvinkenroye University of Stuttgart

Other publications of authors with the same name

Application of noise robust MDT speech recognition on the SPEECON and speechdat-car databases.J. Gemmeke, Y. Wang, M. Segbroeck, B. Cranen, and H. hamme. INTERSPEECH, page 1227-1230. ISCA, (2009)Robust language identification using convolutional neural network features.S. Ganapathy, K. Han, S. Thomas, M. Omar, M. Segbroeck, and S. Narayanan. INTERSPEECH, page 1846-1850. ISCA, (2014)Affective Feature Design and Predicting Continuous Affective Dimensions from Music.N. Kumar, R. Gupta, T. Guha, C. Vaz, M. Segbroeck, J. Kim, and S. Narayanan. MediaEval, volume 1263 of CEUR Workshop Proceedings, CEUR-WS.org, (2014)Improvements to the IBM speech activity detection system for the DARPA RATS program.S. Thomas, G. Saon, M. Segbroeck, and S. Narayanan. ICASSP, page 4500-4504. IEEE, (2015)Speaker verification using simplified and supervised i-vector modeling.M. Li, A. Tsiartas, M. Segbroeck, and S. Narayanan. ICASSP, page 7199-7203. IEEE, (2013)Directly data-derived articulatory gesture-like representations retain discriminatory information about phone categories.V. Ramanarayanan, M. Segbroeck, and S. Narayanan. Computer Speech & Language, (2016)Advances in Missing Feature Techniques for Robust Large-Vocabulary Continuous Speech Recognition.M. Segbroeck, and H. hamme. IEEE Trans. Audio, Speech & Language Processing, 19 (1): 123-137 (2011)Classifying language-related developmental disorders from speech cues: the promise and the potential confounds.D. Bone, T. Chaspari, K. Audhkhasi, J. Gibson, A. Tsiartas, M. Segbroeck, M. Li, S. Lee, and S. Narayanan. INTERSPEECH, page 182-186. ISCA, (2013)Robust speech recognition using missing data techniques in the prospect domain and fuzzy masks.M. Segbroeck, and H. hamme. ICASSP, page 4393-4396. IEEE, (2008)Applying non-negative matrix factorization on time-frequency reassignment spectra for missing data mask estimation.M. Segbroeck, and H. hamme. INTERSPEECH, page 2511-2514. ISCA, (2009)