AI RESEARCH
Syllabic-Structure Decoder for Automatic Speech Recognition in Vietnamese
arXiv CS.CL
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ArXi:2605.27874v1 Announce Type: new Most Automatic Speech Recognition (ASR) systems formulate transcription as a prediction problem over orthographic units such as characters, subwords, or words. Although effective, such representations do not explicitly reflect the phonetic structure of speech and often require large vocabularies to maintain adequate coverage. In this work, we are motivated from the phonemic features of Vietnamese to propose a Syllabic-Structure Decoder for ASR, which models speech at the phoneme level instead of the orthographic level.