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Advancements in Multilingual Speech Technologies for Human-Computer Interaction
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Author(s): R. N. Ravikumar (Marwadi University, Rajkot, India), S. Aarthi (Marwadi University, Rajkot, India), Maryam Ahmad Usmani (Mamun University, Khiva, Uzbekistan), Pappu Kumar Rai (Marwadi University, Rajkot, India), Muhabbat Jumaniyozova (Urgench State University, Urgench, Uzbekistan)and Maqsuda Narboshova (Termez University of Economics and Service, Termez, Uzbekistan)
Copyright: 2026
Pages: 32
Source title:
Advancements in Speech Processing for Human-Computer Interaction
Source Author(s)/Editor(s): Abeer Saber (Damietta University, Egypt), Tamer Z. Emara (Damietta University, Egypt), Mohammad Sultan Mahmud (Shenzhen University, China), Muhammad Azhar (Hong Kong Shue Yan University, Hong Kong)and Esraa Hassan (Kafrelsheikh University, Egypt)
DOI: 10.4018/979-8-3373-3048-8.ch004
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Abstract
The global integration of communication networks increases the demand for multilingual human-computer interaction (HCI) systems. Speech technology innovations that support multiple languages enhance accessibility and usability. This chapter explores how automatic speech recognition (ASR) and text-to-speech (TTS), combined with language models, ena-ble real-time speech translation across diverse accents and linguistic systems. Deep learning and transfer learning help models learn from small, complex language datasets, even under noisy conditions. Practical applications include educational tools, virtual assistants, cus-tomer service, and healthcare. The section also addresses the need for culturally intuitive, unbiased systems through inclusive design and ethical guidelines, promoting linguistic equality. Advances in multilingual speech technology make HCI more inclusive and effec-tive for global users, supporting developers and researchers alike.
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