scholarly journals Description and Classification of Balti Consonant Stop Sounds

2020 ◽  
Vol 6 (1) ◽  
pp. 1-8
Author(s):  
Ghulam Abbas ◽  
Muhammad Bashir
Keyword(s):  
Software Package ◽  
Speech Analysis ◽  
Degree Programs ◽  
Government College ◽  
Physical Features ◽  
Gilgit Baltistan ◽  
Purposive Sample

The study aims to describe and classify consonant stop sounds of the Balti language, which is spoken in Gilgit-Baltistan, Pakistan. In order to describe and classify these sounds, 120 words were selected from literature written in the Balti language. A purposive sample of 20 Balti speakers from 16 to 35 years of age, who were studying in various degree programs at Government College for Boys, Model Town, Lahore and University of Management and Technology, Lahore, was selected to record possible Balti consonant stop sounds. The physical features of each consonant stop sound were carried through the software package for speech analysis in phonetics. The study reveals that there are 15 consonant stop sounds in the Balti language. The study helps document the Balti language, which follows mostly a verbal tradition like many other languages of the region.

scholarly journals Description and Classification of Balti Consonant Stop Sounds

2020 ◽  
Vol 6 (1) ◽  
pp. 01-08
Author(s):  
Ghulam Abbas ◽  
Muhammad Bashir
Keyword(s):  
Software Package ◽  
Speech Analysis ◽  
Degree Programs ◽  
Government College ◽  
Physical Features ◽  
Gilgit Baltistan ◽  
Purposive Sample

The study aims to describe and classify consonant stop sounds of the Balti language, which is spoken in Gilgit-Baltistan, Pakistan. In order to describe and classify these sounds, 120 words were selected from literature written in the Balti language. A purposive sample of 20 Balti speakers from 16 to 35 years of age, who were studying in various degree programs at Government College for Boys, Model Town, Lahore and University of Management and Technology, Lahore, was selected to record possible Balti consonant stop sounds. The physical features of each consonant stop sound were carried through the software package for speech analysis in phonetics. The study reveals that there are 15 consonant stop sounds in the Balti language. The study helps document the Balti language, which follows mostly a verbal tradition like many other languages of the region.

scholarly journals TPVTrack v1.0: a watershed segmentation and overlap correspondence method for tracking tropopause polar vortices

2018 ◽  
Vol 11 (12) ◽  
pp. 5173-5187 ◽  
Author(s):  
Nicholas Szapiro ◽  
Steven Cavallo
Keyword(s):  
Software Package ◽  
Unstructured Grids ◽  
Test Cases ◽  
Watershed Segmentation ◽  
Spatial Characterization ◽  
Modular Software ◽  
Mean Structure ◽  
Spatial Shape ◽  
Physical Features ◽  
Effective Representation

Abstract. A new free modular software package is described for tracking tropopause polar vortices (TPVs) natively on structured or unstructured grids. Motivated by limitations in spatial characterization and time tracking within existing approaches, TPVTrack mimics the expected dynamics of TPVs to represent their (1) spatial structure, with variable shapes and intensities, and (2) time evolution, with mergers and splits. TPVs are segmented from the gridded flow field into spatial objects as restricted regional watershed basins on the tropopause, described by geometric metrics, associated over time by overlap similarity into major and minor correspondences, and tracked along major correspondences. Simplified segmentation and correspondence test cases illustrate some of the appeal, sensitivities, and limitations of TPVTrack, including effective representation of spatial shape and reduced false positive associations in time. Tracked TPVs in more realistic historical conditions are consistent in bulk with expectations of life cycle and mean structure. Individual tracks are less reliable when discriminating among multiple overlaps. Modifications to track other physical features are possible, with each application requiring evaluation.

scholarly journals Automated speech analysis enables MCI diagnosis

2020 ◽  
Author(s):  
Charalambos Themistocleous ◽  
Marie Eckerström ◽  
Dimitrios Kokkinakis
Keyword(s):  
Mini Mental State Examination ◽  
Screening Tool ◽  
Acoustic Properties ◽  
Screening Tools ◽  
Speech Analysis ◽  
Healthy Controls ◽  
Acoustic Feature ◽  
Language Analysis ◽  
State Examination

Mild Cognitive Impairment (MCI) is a condition characterized by cognitive decline greater than expected for an individual's age and education level. In this study, we are investigating whether acoustic properties of speech production can improve the classification of individuals with MCI from healthy controls augmenting the Mini Mental State Examination, a traditional screening tool, with automatically extracted acoustic information. We found that just one acoustic feature, can improve the AUC score (measuring a trade-off between sensitivity and specificity) from 0.77 to 0.89 in a boosting classification task. These preliminary results suggest that computerized language analysis can improve the accuracy of traditional screening tools.

scholarly journals Hierarchical Radar Data Analysis for Activity and Personnel Recognition

2020 ◽  
Vol 12 (14) ◽  
pp. 2237
Author(s):  
Xingzhuo Li ◽  
Zhenghui Li ◽  
Francesco Fioranelli ◽  
Shufan Yang ◽  
Olivier Romain ◽  
...  
Keyword(s):  
Hierarchical Classification ◽  
Recognition Task ◽  
Radar Data ◽  
Energy Curve ◽  
Walking Gait ◽  
Varying Length ◽  
Physical Features ◽  
Target Activity ◽  
Significant Attention

Radar-based classification of human activities and gait have attracted significant attention with a large number of approaches proposed in terms of features and classification algorithms. A common approach in activity classification attempts to find the algorithm (features plus classifier) that can deal with multiple activities analysed in one study such as walking, sitting, drinking and crawling. However, using the same set of features for multiple activities can be suboptimal per activity and not take into account the diversity of kinematic movements that could be captured by diverse features. In this paper, we propose a hierarchical classification approach that uses a large variety of features including but not limited to energy features like entropy and energy curve, physical features like centroid and bandwidth, image-based features like skewness extracted from multiple radar data domains. Feature selection is used at each step of the hierarchical model to select the best set of features to discriminate the target activity from the others, showing improvements with respect to the more conventional approach of using a multiclass model. The proposed approach is validated on a large dataset with 1078 recorded samples of varying length from 5 s to 10 s of experimental data, yielding 95.4% accuracy to classify six activities. The approach is also validated on a personnel recognition task to identify individual subjects from their walking gait, yielding 83.7% accuracy for ten subjects and 68.2% for a significantly larger group of subjects, i.e., 60 people.

scholarly journals Atlas of airborne particles from Kozani area, Northern Greece

2018 ◽  
Vol 40 (3) ◽  
pp. 1421
Author(s):  
A. Iordanidis ◽  
J. Buckman ◽  
A. G. Triantafyllou ◽  
A. Asvesta
Keyword(s):  
Software Package ◽  
Power Plants ◽  
Environmental Scanning Electron Microscopy ◽  
Morphological Characteristics ◽  
Airborne Particles ◽  
Environmental Scanning ◽  
Northern Greece ◽  
Variable Size ◽  
X Ray

During a whole year (March 2003 to February 2004), several filters that capture airborne particles were collected from seven sampling sites spread throughout the Ptolemais-Kozani region (Western Macedonia), northern Greece. Environmental Scanning Electron Microscopy (ESEM), coupled with Energy Dispersive X-Ray analysis (EDX) was employed for the characterisation of the airborne particles. A classification of these airborne particles is attempted in this study. Aerosols with various morphological characteristics (angular, irregular, rounded, spherical, spheroidal, acicular), variable size (mostly between 5ßm and 20pm) and composition (aluminosilicates, oxides, carbonates, sulphates, metallic) were recognized. The airborne particulates were also categorized according to their origin. Geogenie, biogenic, anthropogenic (mainly fly ash released from lignite-fired power plants), carbonaceous and metalliferous (mainly iron and copper enriched) were the main categories. A database of characteristic airborne particles from Kozani area is being created using a simple software package, in order to help similar studies in the future.

scholarly journals Automatic classification of AD versus FTLD pathology using speech analysis in a biologically confirmed cohort

2021 ◽  
Vol 17 (S5) ◽  
Author(s):  
Sunghye Cho ◽  
Sanjana Shellikeri ◽  
Sharon Ash ◽  
Mark Y. Liberman ◽  
Murray Grossman ◽  
...  
Keyword(s):  
Automatic Classification ◽  
Speech Analysis
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