Journal of
Systemics, Cybernetics and Informatics
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ISSN: 1690-4524 (Online)


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Editorial Advisory Board's Chair
William Lesso

Editor-in-Chief
Nagib C. Callaos


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Informatics and Systemics

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Effect of Flow on Cultured Cell at Micro-Pattern of Ridge Lines
Haruka Hino, Shigehiro Hashimoto, Yusuke Shinozaki, Hiromi Sugimoto, Yusuke Takahashi
(pages: 1-7)

Bridging the Semantic and Lexical Webs: Concept-Validating and Hypothesis-Exploring Ontologies for the Nexus-PORTAL-DOORS System
Adam Craig, Seung-Ho Bae, Carl Taswell
(pages: 8-13)

The Learning Science through Theatre Initiative in the Context of Responsible Research and Innovation
Zacharoula Smyrnaiou, Elena Georgakopoulou, Menelaos Sotiriou, Sofoklis Sotiriou
(pages: 14-22)

Perceptions and Preferences of High School Students in STEM: A Case Study in Connecticut and Mississippi
Bin (Brenda) Zhou, Clifford Anderson, Feng Wang, Lin Li
(pages: 23-26)

A Study on the Meaning of the ‘Lifelong Learning to Be’ Implicated in the Philosophy of Nietzsche
Kwanchun Lee, Soo Yeon Choi, Un Shil Choi
(pages: 27-32)

Barriers to Social Innovation and Ways of Overcoming them in Latvia
Karine Oganisjana, Yuliya Eremina, Salome Gvatua, Benjamin Ngongo Kabwende, Ozoemena Joseph Chukwu
(pages: 33-38)

Unmanned Aerial Vehicle-Based Automobile License Plate Recognition System for Institutional Parking Lots
Julian Dasilva, Ricardo Jiménez, Roland Schiller, Sanja Zivanovic González
(pages: 39-43)

Dialectal Atlas of the Arab World - between Intention and Reality
Oleg Redkin, Olga Bernikova
(pages: 44-47)

IT Risk and Chaos Theory: Effect on the Performance of South African SMEs
Anass Bayaga, Stephen Flowerday, Liezel Cilliers
(pages: 48-53)

How to Apply the User Profile Usability Technique in the User Modelling Activity for an Adaptive Food Recommendation System for People on Special Diets
Lucrecia Llerena, Nancy Rodríguez, Pablo Gómez-Abajo, John W. Castro
(pages: 54-63)

Policies, Legislation and Regulatory Compliance Governance Impact on Strategic Management of Higher Education and Research Institutions in Latvia
Anita Straujuma, Inga Lapina, Elina Gaile-Sarkane, Modris Ozolins
(pages: 64-69)

Parallel Prediction of Stock Volatility
Priscilla Jenq, John Jenq
(pages: 70-73)

Hacking a Bridge: An Exploratory Study of Compliance-Based Information Security Management in Banking Organization
Tesleem Fagade, Theo Tryfonas
(pages: 74-80)

Improvement in the Physical and Psychological Well-Being of Persons with Spinal Cord Injuries by Means of Powered Wheelchairs Driven by Dual Power Wheels and Mobile Technologies
Yee-Pien Yang, Li-Jen Weng, Ye-Yu Yeh, Hui-Fen Mao, Ray-I. Chang
(pages: 81-87)

Data Mediation with Enterprise Level Security
Kevin E. Foltz, William R. Simpson
(pages: 88-93)


 

Abstracts

 


ABSTRACT


Identification of Hindi Dialects and Emotions using Spectral and Prosodic features of Speech

K Sreenivasa Rao, Shashidhar G. Koolagudi


In this paper, we have explored speech features to identify Hindi dialects and emotions. A dialect is any distinguishable variety of a language spoken by a group of people. Emotions provide naturalness to speech. In this work, five prominent dialects of Hindi are considered for the identification task. They are Chattisgharhi (spoken in central India), Bengali (Bengali accented Hindi spoken in Eastern region), Marathi (Marathi accented Hindi spoken in Western region), General (Hindi spoken in Northern region) and Telugu (Telugu accented Hindi spoken in Southern region). Along with dialect identification, we have also carried out emotion recognition in this work. Speech database considered for dialect identification task consists of spontaneous speech spoken by male and female speakers. Indian Institute of Technology Kharagpur Simulated Emotion Hindi Speech Corpus (IITKGP-SEHSC) is used for conducting the emotion recognition studies. The emotions considered in this study are anger, disgust, fear, happy, neutral and sad. Prosodic and spectral features extracted from speech are used for discriminating the dialects and emotions. Spectral features are represented by Mel frequency cepstral coefficients (MFCC) and prosodic features are represented by durations of syllables, pitch and energy contours. Auto-associative neural network (AANN) models and Support Vector Machines (SVM) are explored for capturing the dialect specific and emotion specific information from the above specified features. AANN models are expected to capture the nonlinear relations specific to dialects or emotions through the distributions of feature vectors. SVMs perform dialect or emotion classification based on discriminative characteristics present among the dialects or emotions. Classification systems are developed separately for dialect classification and emotion classification. Recognition performance of the dialect identification and emotion recognition systems is found to be 81% and 78% respectively.

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