Match!
Prasanna V. Kothalkar
University of Texas at Dallas
8Publications
3H-index
35Citations
Publications 8
Newest
#1Jun Wang (UTD: University of Texas at Dallas)H-Index: 15
Last.Jordan R. Green (MGH Institute of Health Professions)H-Index: 28
view all 9 authors...
AbstractPurpose: This research aimed to automatically predict intelligible speaking rate for individuals with Amyotrophic Lateral Sclerosis (ALS) based on speech acoustic and articulatory samples.Method: Twelve participants with ALS and two normal subjects produced a total of 1831 phrases. NDI Wave system was used to collect tongue and lip movement and acoustic data synchronously. A machine learning algorithm (i.e. support vector machine) was used to predict intelligible speaking rate (speech in...
Sep 2, 2018 in INTERSPEECH (Conference of the International Speech Communication Association)
#1Prasanna V. Kothalkar (UTD: University of Texas at Dallas)H-Index: 3
#2Johanna M. Rudolph (UTD: University of Texas at Dallas)H-Index: 2
Last.John H. L. Hansen (UTD: University of Texas at Dallas)H-Index: 48
view all 6 authors...
#1Prasanna V. Kothalkar (UTD: University of Texas at Dallas)H-Index: 3
#2Johanna M. Rudolph (UTD: University of Texas at Dallas)H-Index: 2
Last.John H. L. Hansen (UTD: University of Texas at Dallas)H-Index: 48
view all 6 authors...
Jul 1, 2018 in EMBC (International Conference of the IEEE Engineering in Medicine and Biology Society)
#1Prasanna V. Kothalkar (UTD: University of Texas at Dallas)H-Index: 3
#2Johanna M. Rudolph (UTD: University of Texas at Dallas)H-Index: 2
Last.John H. L. Hansen (UTD: University of Texas at Dallas)H-Index: 48
view all 6 authors...
Pediatric speech sound disorders (SSD) encompass a wide range of speech production deficits that can interfere with children’s educational growth, social engagement and employment opportunities. Early detection of SSDs can facilitate timely intervention and minimize the potential for life-long adverse effects, but distinguishing between typical and atypical speech production in preschoolers is challenging due to developmental and individual variability in speech acquisition. In this study we app...
Sep 8, 2016 in INTERSPEECH (Conference of the International Speech Communication Association)
#1Jun WangH-Index: 15
#2Prasanna V. Kothalkar (UTD: University of Texas at Dallas)H-Index: 3
Last.Daragh HeitzmanH-Index: 7
view all 4 authors...
#1Tahrima Rahman (UTD: University of Texas at Dallas)H-Index: 3
#2Prasanna V. Kothalkar (UTD: University of Texas at Dallas)H-Index: 3
Last.Vibhav Gogate (UTD: University of Texas at Dallas)H-Index: 17
view all 3 authors...
In this paper, we present cutset networks, a new tractable probabilistic model for representing multi-dimensional discrete distributions. Cutset networks are rooted OR search trees, in which each OR node represents conditioning of a variable in the model, with tree Bayesian networks (Chow-Liu trees) at the leaves. From an inference point of view, cutset networks model the mechanics of Pearl's cutset conditioning algorithm, a popular exact inference method for probabilistic graphical models. We p...
1