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Cued Speech (CS) is a multi-modal visual coding system combining lip readingwith several hand cues at the phonetic level to make the spoken languagevisible to the hearing impaired. Previous studies solved asynchronous problemsbetween lip and hand movements by a cuer\footnote{The people who perform CuedSpeech are called the cuer.}-dependent piecewise linear model for English andFrench CS. In this work, we innovatively propose three statistical measure onthe lip stream to build an interpretable and generalizable model for predictinghand preceding time (HPT), which achieves cuer-independent by a propernormalization. Particularly, we build the first Mandarin CS corpus comprisingannotated videos from five speakers including three normal and two hearingimpaired individuals. Consequently, we show that the hand preceding phenomenonexists in Mandarin CS production with significant differences between normaland hearing impaired people. Extensive experiments demonstrate that our modeloutperforms the baseline and the previous state-of-the-art methods.

A Novel Interpretable and Generalizable Re-synchronization Model for Cued Speech based on a Multi-Cuer Corpus