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      Automatic Speech Recognition and Translation for Low Resource Languages

      AvL. Ashok Kumar,D. Karthika Renuka

      Inbunden, Engelska, 2024

      2 478 kr

      Beställningsvara. Skickas inom 5-8 vardagar. Fri frakt över 249 kr.

      Beskrivning

      AUTOMATIC SPEECH RECOGNITION and TRANSLATION for LOW-RESOURCE LANGUAGES This book is a comprehensive exploration into the cutting-edge research, methodologies, and advancements in addressing the unique challenges associated with ASR and translation for low-resource languages. Automatic Speech Recognition and Translation for Low Resource Languages contains groundbreaking research from experts and researchers sharing innovative solutions that address language challenges in low-resource environments. The book begins by delving into the fundamental concepts of ASR and translation, providing readers with a solid foundation for understanding the subsequent chapters. It then explores the intricacies of low-resource languages, analyzing the factors that contribute to their challenges and the significance of developing tailored solutions to overcome them. The chapters encompass a wide range of topics, ranging from both the theoretical and practical aspects of ASR and translation for low-resource languages. The book discusses data augmentation techniques, transfer learning, and multilingual training approaches that leverage the power of existing linguistic resources to improve accuracy and performance. Additionally, it investigates the possibilities offered by unsupervised and semi-supervised learning, as well as the benefits of active learning and crowdsourcing in enriching the training data. Throughout the book, emphasis is placed on the importance of considering the cultural and linguistic context of low-resource languages, recognizing the unique nuances and intricacies that influence accurate ASR and translation. Furthermore, the book explores the potential impact of these technologies in various domains, such as healthcare, education, and commerce, empowering individuals and communities by breaking down language barriers. Audience The book targets researchers and professionals in the fields of natural language processing, computational linguistics, and speech technology. It will also be of interest to engineers, linguists, and individuals in industries and organizations working on cross-lingual communication, accessibility, and global connectivity.

      Produktinformation

      • Utgivningsdatum:2024-05-03
      • Vikt:989 g
      • Format:Inbunden
      • Språk:Engelska
      • Antal sidor:496
      • Förlag:John Wiley & Sons Inc
      • ISBN:9781394213580

      Utforska kategorier

      • Artificiell intelligens inom Data och IT

      Mer om författaren

      L. Ashok Kumar, PhD, is a professor in the Department of Electrical and Electronics Engineering, PSG of Technology, Tamil Nadu, India. He has published more than 175 papers in international and national journals and received 26 awards for his PhD project on wearable electronics at national and international levels. He has created eight Centres of Excellence at PSG in collaboration with government agencies and industries such as the Centre for Audio Visual Speech Recognition and the Centre for Excellence in Solar Thermal Systems. Twenty-three out of 27 of his products have been technologically transferred to government funding agencies. D. Karthika Renuka, PhD, is a professor at PSG of Technology, Tamil Nadu, India. Her main areas of study focus on data mining, evolutionary algorithms, and machine learning. She is a recipient of the Indo-U.S. Fellowship for Women in STEMM. She has organized two international conferences on The Innovation of Computing Techniques and Information Processing and Remote Computing. Bharathi Raja Chakravarthi, PhD, is an assistant professor in the School of Computer Science, University of Galway, Ireland. His studies focus on multimodal machine learning, abusive/offensive language detection, bias in natural language processing tasks, inclusive language detection, and multilingualism. He has published many papers in international journals and conferences. He is an associate editor of the journal Expert System with Application and an editorial board member for Computer Speech & Language. Thomas Mandl, PhD, is a professor of Information Science and Language Technology, University of Hildesheim, Germany. His research interests include information retrieval, human-computer interaction, and internationalization of information technology and he has published more than 300 papers on these topics. He coordinated tracks at the Cross Language Evaluation Forum (CLEF), the European information retrieval evaluation initiative. Thomas Mandl is the co-chair at FIRE, the evaluation initiative for Indian languages, since 2020 and coordinates the HASOC track on hate speech detection.

      Innehållsförteckning

      • Foreword xixPreface xxiAcknowledgement xxiii1 A Hybrid Deep Learning Model for Emotion Conversion in Tamil Language 1Satrughan Kumar Singh, Muniyan Sundararajan and Jainath Yadav2 Attention-Based End-to-End Automatic Speech Recognition System for Vulnerable Individuals in Tamil 15S. Suhasini, B. Bharathi and Bharathi Raja Chakravarthi3 Speech-Based Dialect Identification for Tamil 27Archana J.P. and B. Bharathi4 Language Identification Using Speech Denoising Techniques: A Review 41Amal Kumar, Piyush Kumar Singh and Jainath Yadav5 Domain Adaptation-Based Self-Supervised ASR Models for Low-Resource Target Domain 51L. Ashok Kumar, D. Karthika Renuka, Naveena K. S. and Sree Resmi S.6 ASR Models from Conventional Statistical Models to Transformers and Transfer Learning 69Elizabeth Sherly, Leena G. Pillai and Kavya Manohar7 Syllable-Level Morphological Segmentation of Kannada and Tulu Words 113Asha Hegde and Hosahalli Lakshmaiah Shashirekha8 A New Robust Deep Learning-Based Automatic Speech Recognition and Machine Transition Model for Tamil and Gujarati 135Monesh Kumar M. K., Valliammai V., Geraldine Bessie Amali D. and Mathew M. Noel9 Forensic Voice Comparison Approaches for Low-Resource Languages 155Kruthika S.G., Trisiladevi C. Nagavi and P. Mahesha10 CoRePooL--Corpus for Resource-Poor Languages: Badaga Speech Corpus 193Barathi Ganesh H.B., Jyothish Lal G., Jairam R., Soman K.P., Kamal N.S. and Sharmila B.11 Bridging the Linguistic Gap: A Deep Learning-Based Image- to-Text Converter for Ancient Tamil with Web Interface 213S. Umamaheswari, G. Gowtham and K. Harikumar12 Voice Cloning for Low-Resource Languages: Investigating the Prospects for Tamil 243Vishnu Radhakrishnan, Aadharsh Aadhithya A., Jayanth Mohan, Visweswaran M., Jyothish Lal G. and Premjith B.13 Transformer-Based Multilingual Automatic Speech Recognition (ASR) Model for Dravidian Languages 259Divi Eswar Chowdary, Rahul Ganesan, Harsha Dabbara, G. Jyothish Lal and Premjith B.14 Language Detection Based on Audio for Indian Languages 275Amogh A. M., A. Hari Priya, Thanvitha Sai Kanchumarti, Likhitha Ram Bommilla and Rajeshkannan Regunathan15 Strategies for Corpus Development for Low-Resource Languages: Insights from Nepal 297Bal Krishna Bal, Balaram Prasain, Rupak Raj Ghimire and Praveen Acharya16 Deep Neural Machine Translation (DNMT): Hybrid Deep Learning Architecture-Based English-to-Indian Language Translation 331Nivaashini M., Priyanka G. and Aarthi S.17 Multiview Learning-Based Speech Recognition for Low-Resource Languages 375Aditya Kumar and Jainath Yadav18 Automatic Speech Recognition Based on Improved Deep Learning 405Kingston Pal Thamburaj and Kartheges Ponniah19 Comprehensive Analysis of State-of-the-Art Approaches for Speaker Diarization 427Trisiladevi C. Nagavi, Samanvitha S., Shreya Sudhanva, Sukirth Shivakumar and Vibha Hullur20 Spoken Language Translation in Low-Resource Language 445S. Shoba, Sasithradevi A. and S. DeepaReferences 456
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