Advancements in Speech Processing for Human-Computer Interaction

Speech processing technologies are revolutionizing human-computer interaction by enabling machines to understand and respond to natural language with greater accuracy and nuance. This progress enhances accessibility, supports inclusiveness, and creates more seamless digital experiences across education, healthcare, and daily life. As voice-driven systems become more integrated into society, they have the potential to transform communication, productivity, and even social connectedness. At the same time, they introduce critical considerations around ethics, privacy, and the responsible use of AI in human interaction. Advancements in Speech Processing for Human-Computer Interaction provides a comprehensive and up-to-date analysis of the latest breakthroughs in speech processing, specifically focusing on their applications and impact within the field of human-computer interaction. It goes beyond a mere survey of existing technologies, providing a critical analysis of the latest advancements, highlighting their practical implications, and inspiring future research and innovation in the exciting and rapidly evolving field of speech-enabled human-computer interaction. Covering topics such as artificial empathy, natural language processing, and social media, this book is an excellent resource for researchers, developers, graduate and postgraduate students, industry professionals, product managers, academicians, and more.

Abeer Saber was born in Damietta, Dumyat, Egypt, in 1992. She received the B.Sc. Degree in Computer Science and the M.Sc. Degree in Computer Science from Mansoura University, Egypt, in 2013 and 2018, respectively. She is received the Ph.D. in computer science from Menoufia University, Egypt, in 2022. She is currently a Lecturer in information technology with the Faculty of Computers and Artificial intelligence, Damietta University, Egypt. She has published many research articles in prestigious international conferences and reputable journals. She is also a reviewer for many journals. Her current research interests include big data analysis, semantic web, linked open data, Optimization, machine learning, Deep learning, bioinformatics, and IoT.

Tamer Emara holds a Ph.D. in Information and Communication Engineering from Shenzhen University, China, and is an Assistant Professor at the Faculty of Computers and Artificial Intelligence, Damietta University, Egypt. He earned his M.Sc. and B.Sc. degrees from Mansoura and Tanta Universities, respectively. Dr. Emara has received numerous awards, including the Excellent Paper Award from the Big Data Mining and Analytics journal in 2021, the Outstanding Scientific Award from the Higher Institute of Engineering and Technology Kafrelsheikh, the Shenzhen Universiade International Scholarship, and recognition as the Outstanding Doctoral Student of Shenzhen University in 2016. Dr. Emara is actively engaged in the academic community, serving as Program Committee Chair for the 2025 IEEE International Conference on Computer Science, Technology, and Engineering (ICCSTE2025) in Wuhan, China, and as General Chair for the 2024 International Conference on Artificial Intelligence and Mechanical Engineering (ICAIME2024) in Nanjing, China. He also contributes as a member of the Technical Program Committee (TPC) and Organization Committees for various conferences and serves as a reviewer for multiple journals. Dr. Emara is a senior member of the IEEE and a member of the ACM. His research interests span big data management and applications, machine learning, distributed and parallel computing, bioinformatics, and IoT.

Mohammad Sultan Mahmud (Senior Member, IEEE) received the Ph.D. degree from Shenzhen University, China, in 2023, and the master’s degree from King Mongkut’s University of Technology North Bangkok, Thailand, in 2014. Currently, Dr. Mahmud is a Research Fellow with the College of Computer Science and Software Engineering, Shenzhen University, China. He is one of the pioneers in the distributed clustering ensemble of big data research. Dr. Mahmud has published research articles in esteemed journals such as Information Fusion, IEEE Transactions on Big Data, Big Data Mining and Analytics, and the Journal of Big Data. He has organized a special issue on “Mixture of Experts (MoE) and Ensemble Learning for Big Data” in Information Fusion (Elsevier). His current research focuses on big data mining, distributed and parallel computing, ensemble learning, and mixture of experts.

Dr. Muhammad Azhar is the Associate Head of Department and Director of BSc-ADS programme of Applied Data Science and Assistant Professor at Hong Kong Shue Yan University, SAR, China. He is also the Director of Big Data Laboratory of HKSYU. Before joining HKSYU as an Assistant Professor in 2023, Dr. Azhar has over 11 years of experience in teaching and research in different universities and research institutes in South Korea, Mainland China and Pakistan. In addition to this, he worked in different software companies of Pakistan (Sofnix Private Limited and Turnotech Private Limited) and U.K. (Welltime Ltd.). He received his B.S. degree in Computer Science from National University of Computer and Emerging Sciences, Islamabad, Pakistan, master’s degree in computer science from Sejong University, Seoul, South Korea, and the Ph.D. degree in Machine Learning and Data Mining from Shenzhen University, Shenzhen, China. He worked as a Research Professor at Chosun University, South Korea. His research interests include Data Mining, Natural Language Processing and Computer Vision through conventional machine learning and advanced deep learning techniques.

Esraa Hassan was born in Kafrelsheikh, Kafrelsheikh, Egypt, in 1992. She received a B.Sc. Degree in Computer Science and a M.Sc. Degree in Computer Science from Mansoura University, Egypt, in 2013 and 2018, respectively. She received her Ph.D. in computer science from Mansoura University, Egypt, in 2022. She is currently a lecturer at the Faculty of Artificial Intelligence, Kafrelsheikh University, Egypt. She has published many research articles in prestigious international conferences and reputable journals. She is also a reviewer for many journals. Her research interests include machine learning, deep learning, optimization, and bioinformatics.