Abstract
Punctuation marks in text usually tend to be taken as breath pauses. However, not all pauses occur at punctuation marks, and, in fact, not all punctuations are designed to be pauses. In this paper, we introduce a method for suggesting speech pauses for a given script submitted by English language learners. In our approach, a text is transformed into a non-punctuated text with features aimed at suggesting appropriate pauses in speech. The method involves automatically generating training data annotated with pauses, automatically transform the training data into linguistic features, and automatically training a discriminative classifier. Evaluation shows that the proposed method achieves a satisfactory performance in suggesting pauses in given speech.