In　this　paper,　we　study　the　local　constant　and　the　local　linear　estimators　of　the　conditional　density　function　with　right-censored　data　which　exhibit　some　type　of　dependence.　It　is　assumed　that　the　observations　form　a　stationary　(Formula　presented.)　mixing　sequence.　The　asymptotic　normality　of　the　two　estimators　is　established,　which　combined　with　the　condition　that　(Formula　presented.)　implies　the　consistency　of　the　two　estimators　and　can　be　employed　to　construct　confidence　intervals　for　the　conditional　density　function.　The　result　on　the　local　linear　estimator　of　the　conditional　density　function　in　Kim　et al.　(2010)　is　relaxed　from　the　i.i.d.　assumption　to　the　(Formula　presented.)　mixing　setting,　and　the　result　on　the　local　linear　estimator　of　the　conditional　density　function　in　Spierdijk　(2008)　is　relaxed　from　the　ρ-mixing　assumption　to　the　(Formula　presented.)　mixing　setting.　Finite　sample　behavior　of　the　estimators　is　investigated　by　simulations.　©　2019　Taylor　&　Francis　Group,　LLC.