Izzad Ramli

Papers

Total Citations

H-Index

About

Izzad Ramli is a pioneering researcher in Malay language speech technology, with a focused expertise in text-to-speech (TTS) synthesis for human-robot interaction. His work centers on developing natural, expressive speech systems for humanoid robots and storytelling applications. Ramli’s most impactful contribution is his 2015 paper on improved syllabification for Malay TTS, which has garnered 35 citations—a significant achievement in a specialized field. This work addresses a core challenge in speech synthesis: producing accurate syllabic units essential for generating human-like speech. He further advanced the field by creating the first Malay language storytelling TTS corpus, a carefully curated dataset of 464 sentences from children’s stories, enabling expressive speech synthesis for humanoid storytellers. His rule-based approach to storytelling TTS synthesis tackles the growing demand for emotionally nuanced speech in applications ranging from talking books to interactive robots. Through these contributions, Ramli has established foundational resources and methodologies for Malay speech synthesis, directly supporting the development of more natural and engaging human-computer interaction in Southeast Asian languages.