Noraini Seman

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About

Noraini Seman is a leading researcher in Malay language speech technology, with a primary focus on text-to-speech (TTS) synthesis for human-robot interaction. Her work centers on developing natural, expressive speech systems that bridge the gap between computational linguistics and humanoid robotics. Seman’s most cited paper, “An Improved Syllabification for a Better Malay Language Text-to-Speech Synthesis (TTS)” (2015, 35 citations), established a foundational method for generating accurate syllabic speech units—a critical step toward producing human-like speech in Malay. She further advanced the field by creating the first Malay language storytelling TTS corpus (2018), a carefully curated dataset of 464 sentences and over 9,500 syllables designed specifically for humanoid storytellers. Her rule-based approach to expressive speech synthesis (2016) addressed the growing demand for emotionally nuanced output in applications like talking books and interactive robots. Through these contributions, Seman has positioned herself at the forefront of Malay speech synthesis, enabling more natural communication between humans and machines. Her work not only advances TTS technology but also preserves and promotes the Malay language in the digital age, making her research invaluable for developers of educational robots, assistive technologies, and culturally-aware AI systems.