| 1 |
Deep Neural Network Model of Hearing-Impaired Speech-in-Noise Performance
|
|
|
|
In: Frontiers (2020)
|
|
BASE
|
|
Show details
|
|
|
| 2 |
A Framework for Biomarkers of COVID-19 Based on Coordination of Speech-Production Subsystems
|
|
|
|
In: IEEE (2020)
|
|
BASE
|
|
Show details
|
|
|
| 3 |
Deep Neural Network Model of Hearing-Impaired Speech-in-Noise Perception
|
|
|
|
In: Front Neurosci (2020)
|
|
BASE
|
|
Show details
|
|
|
| 4 |
Assessment of speech and fine motor coordination in children with autism spectrum disorder
|
|
|
|
In: IEEE Access (2020)
|
|
BASE
|
|
Show details
|
|
|
| 5 |
Data from: Speed-accuracy tradeoffs in human speech production ...
|
|
|
|
Abstract:
Speech motor actions are performed quickly, while simultaneously maintaining a high degree of accuracy. Are speed and accuracy in conflict during speech production? Speed-accuracy tradeoffs have been shown in many domains of human motor action, but have not been directly examined in the domain of speech production. The present work seeks evidence for Fitts’ law, a rigorous formulation of this fundamental tradeoff, in speech articulation kinematics by analyzing USC-TIMIT, a real-time magnetic resonance imaging data set of speech production. A theoretical framework for considering Fitts’ law with respect to models of speech motor control is elucidated. Methodological challenges in seeking relationships consistent with Fitts’ law are addressed, including the operational definitions and measurement of key variables in real-time MRI data. Results suggest the presence of speed-accuracy tradeoffs for certain types of speech production actions, with wide variability across syllable position, and substantial ... : Imaging based data of Human Speech articulation to investigate speed-accuracy tradeoffs in speech productionAuthors: Lammert, A., Shadle, C., Narayanan, S. & Quatieri, T. Date 23.Aug.2018 The files contained in this directory represent data that were used to produce the results described in the PLOS ONE article ``Speed-Accuracy Tradeoffs in Human Speech Production’’ by Lammert, A., Shadle, C., Narayanan, S. & Quatieri, T.complexity_mats_plos.zip ...
|
|
URL: https://dx.doi.org/10.5061/dryad.5pn163j
http://datadryad.org/stash/dataset/doi:10.5061/dryad.5pn163j
|
|
BASE
|
|
Hide details
|
|
|
| 8 |
Evaluation of Glottal Inverse Filtering Algorithms Using a Physiologically Based Articulatory Speech Synthesizer
|
|
|
|
In: IEEE/ACM Trans Audio Speech Lang Process (2017)
|
|
BASE
|
|
Show details
|
|
|
| 9 |
Neurophysiological Vocal Source Modeling for Biomarkers of Disease
|
|
|
|
In: Ghosh (2016)
|
|
BASE
|
|
Show details
|
|
|
| 10 |
Phonologically-based biomarkers for major depressive disorder
|
|
|
|
BASE
|
|
Show details
|
|
|
| 12 |
Towards Interpretive Models for 2-D Processing of Speech
|
|
|
|
In: DTIC (2011)
|
|
BASE
|
|
Show details
|
|
|
| 13 |
Phonologically-Based Biomarkers for Major Depressive Disorder
|
|
|
|
In: DTIC (2011)
|
|
BASE
|
|
Show details
|
|
|
| 14 |
Investigating acoustic correlates of human vocal fold vibratory phase asymmetry through modeling and laryngeal high-speed videoendoscopya
|
|
|
|
BASE
|
|
Show details
|
|
|
| 16 |
Towards co-channel speaker separation BY 2-D demodulation of spectrograms
|
|
|
|
In: IEEE (2009)
|
|
BASE
|
|
Show details
|
|
|
| 17 |
Towards Co-Channel Speaker Separation by 2-D Demodulation of Spectrograms
|
|
|
|
In: DTIC (2009)
|
|
BASE
|
|
Show details
|
|
|
| 19 |
2-D Processing of Speech with Application to Pitch and Formant Estimation
|
|
|
|
In: DTIC (2007)
|
|
BASE
|
|
Show details
|
|
|
|
|
