Speech　pauses　are　considered　as　punctuation　marks　of　spoken　language.　People　always　insert　different　pauses　at　the　boundaries　of　rhythmic　phrases　when　communicating　by　language.　Based　on　this　characteristic,　the　speech　pause　of　punctuation　marks　is　investigated　and　the　concept　of　predicting　speech　pauses　using　punctuation　information　is　proposed.　The　punctuation-based　and　SLM-based　methods　are　introduced　to　obtain　training　corpus　and　predict　speech　pauses.　The　influence　of　training　corpus　size　on　the　performance　of　model　is　discussed.　And　the　performance　of　punctuation-based　corpus　and　manually-labeled　corpus　is　compared.　Experimental　results　show　that　the　Chinese　punctuation　supplies　valuable　information　on　pause,　and　the　method　based　on　punctuation　information　can　predict　the　Chinese　speech　pauses　effectively.