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Applying AI-Based Tools and Technologies Towards Revitalization of Indigenous and Endangered Languages

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Description

This book emphasises the need for language resource development and its impact on society. It covers latest AI based tools and techniques used to preserve indigenous and endangered languages. The book also highlights latest AI based technologies such as Generative Pre-trained Transformer (GPT) towards endangered language preservation. It discusses morphology analysis, translation support and shallow parsing of various tribal languages of India and abroad. This book tries to answer how digital technologies can make language revitalization accessible to future generations.

Détails

Autres ISBN/GTIN9789819719877
Type de produitE-book
ReliureE-book
FormatPDF
Indications sur le formatfiligrane
Date de parution23.04.2024
Edition24001 A. 2024
SérieStudies in Computational Intelligence
No. de série1148
Pages220 pages
LangueAnglais
Taille fichier4073 Kbytes
IllustrationsXIV, 220 p. 69 illus., 25 illus. in color.
N° article50310981
CataloguesVC
Source des données n°5137773
Plus de détails

Série

Auteur

Dr. Sushree Sangita Mohanty currently working as an Assistant Professor in the department of

Anthropology as well as leading the project Mother Tongue based Multilingual Education at Kalinga

Institute of Social Sciences (KISS) which has recently received the UNESCO International Literary

Prize 2022. Her expertise in Multilingual Education facilitates easing the process to build a strong

educational foundation among the indigenous children of KISS. Her research interests are

multidisciplinary in nature which centres around socio-cultural life, multilingualism and livelihood

vulnerability of indigenous & low-income communities of Odisha/India. She has been listed as a

UNESCO Inclusive Policy Lab Expert.



Dr. Satya Ranjan Dash is currently working as an associate professor at KIIT University, India. His

current research includes Epileptic Seizure Detection based on EEG Signal through Spiking neural

network (SNN), Classification of Schizophrenia Patients from EEG and fMRI using SNN and SSN,

fetal heart rate signals classification through extreme learning machine (ELM), Mammogram

Analysis with Local binary pattern (LBP), generative adversarial network (GAN) model, Machine

Learning , Medical Image Processing, Machine Translation, Natural Language Processing and Fuzzy

Mathematical Models.



Dr. Shantipriya Parida currently working as a Senior AI Scientist at Silo AI, Finland. Before joining

Silo AI, Shantipriya worked as a Postdoctoral Researcher at Idiap Research Institute, Switzerland.

He has obtained his Postdoc in Machine Translation from Charles University, Prague, Czech

Republic, Ph.D. in Computational Neuroscience from Utkal University, Odisha, India. Before joining

postdoc at Charles University, he worked as a System Architect at Huawei Technologies India Pvt

Ltd, Bangalore, India. He has 15 years of experience in software development and architecture, as

well as expertise in machine learning, deep learning, and Natural Language Processing. He has 4

years of research experience in leading NLP tasks in EU H2020 and InnoSuisse projects with

publications in top-tier conferences and journals. He is part of the program committee/organizer

for many top-tier NLP conferences and workshops. Recently published an edited book "Natural

Language Processing in Healthcare: A Special Focus on Low Resource Language" in collaboration

with other NLP researchers.

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