Okko Räsänen
Okko Räsänen
Associate Professor, Academy Research Fellow, Tampere University, Finland
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Zitiert von
Zitiert von
Feature selection methods and their combinations in high-dimensional classification of speaker likability, intelligibility and personality traits
J Pohjalainen, O Räsänen, S Kadioglu
Computer Speech & Language 29 (1), 145-171, 2015
Random subset feature selection in automatic recognition of developmental disorders, affective states, and level of conflict from speech.
O Räsänen, J Pohjalainen
Interspeech, 210-214, 2013
Sequence prediction with sparse distributed hyperdimensional coding applied to the analysis of mobile phone use patterns
OJ Räsänen, JP Saarinen
IEEE transactions on neural networks and learning systems 27 (9), 1878-1889, 2015
An improved speech segmentation quality measure: the R-value
OJ Räsänen, UK Laine, T Altosaar
Tenth Annual Conference of the International Speech Communication Association, 2009
Unsupervised word discovery from speech using automatic segmentation into syllable-like units
O Räsänen, G Doyle, MC Frank
Interspeech–2015, 2015
Computational modeling of phonetic and lexical learning in early language acquisition: Existing models and future directions
O Räsänen
Speech Communication 54 (9), 975-997, 2012
A joint model of word segmentation and meaning acquisition through cross-situational learning.
O Räsänen, H Rasilo
Psychological review 122 (4), 792, 2015
Pre-linguistic segmentation of speech into syllable-like units
O Räsänen, G Doyle, MC Frank
Cognition 171, 130-150, 2018
Modeling dependencies in multiple parallel data streams with hyperdimensional computing
O Räsänen, S Kakouros
IEEE Signal Processing Letters 21 (7), 899-903, 2014
A thorough evaluation of the Language Environment Analysis (LENA) system
A Cristia, M Lavechin, C Scaff, M Soderstrom, C Rowland, O Räsänen, ...
Behavior Research Methods 53 (2), 467-486, 2021
Automatic posture and movement tracking of infants with wearable movement sensors
M Airaksinen, O Räsänen, E Ilén, T Häyrinen, A Kivi, V Marchi, A Gallen, ...
Scientific reports 10 (1), 1-13, 2020
A computational model of word segmentation from continuous speech using transitional probabilities of atomic acoustic events
O Räsänen
Cognition 120 (2), 149-176, 2011
Development of a novel robust measure for interhemispheric synchrony in the neonatal EEG: activation synchrony index (ASI)
O Räsänen, M Metsäranta, S Vanhatalo
Neuroimage 69, 256-266, 2013
Early development of synchrony in cortical activations in the human
N Koolen, A Dereymaeker, O Räsänen, K Jansen, J Vervisch, V Matic, ...
Neuroscience 322, 298-307, 2016
A method for noise-robust context-aware pattern discovery and recognition from categorical sequences
O Räsänen, UK Laine
Pattern Recognition 45 (1), 606-616, 2012
Interhemispheric synchrony in the neonatal EEG revisited: activation synchrony index as a promising classifier
N Koolen, A Dereymaeker, O Räsänen, K Jansen, J Vervisch, V Matic, ...
Frontiers in human neuroscience 8, 1030, 2014
Perception of sentence stress in speech correlates with the temporal unpredictability of prosodic features
S Kakouros, O Räsänen
Cognitive science 40 (7), 1739-1774, 2016
Blind segmentation of speech using non-linear filtering methods
O Räsänen, UK Laine, T Altosaar
Speech Technologies, 105-124, 2011
Is infant-directed speech interesting because it is surprising?–Linking properties of IDS to statistical learning and attention at the prosodic level
O Räsänen, S Kakouros, M Soderstrom
Cognition 178, 193-206, 2018
3PRO–An unsupervised method for the automatic detection of sentence prominence in speech
S Kakouros, O Räsänen
Speech Communication 82, 67-84, 2016
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