Target　speaker　extraction　(TSE)　is　a　practical　solution　to　the　cocktail　party　problem.　Recently,　a　novel　embedding-free　TSE　method　was　proposed.　In　this　method,　the　enrollment　and　the　mixed　signal　are　directly　interacted　to　exploit　the　contextual　information　within　the　enrollment.　In　the　absence　of　noise,　the　derived　guidance　exhibits　the　onset,　offset　and　voice　activity　similar　to　the　mixed　signal.　However,　in　the　presence　of　noise,　such　similarity　may　be　destroyed　since　the　enrollment　is　interacted　with　both　speech　and　noise　signals　in　the　mixture.　If　the　noise　(e.g.,　babble　noise)　contains　components　that　resemble　the　enrollment　to　some　extent,　the　misleading　guidance　may　be　generated　after　the　direct　interaction.　To　tackle　this　issue,　an　additional　enhancer　is　designed　in　this　paper　to　derive　an　auxiliary　guidance　that　emphasizes　the　active　speech.　Specifically,　this　enhancer　consists　of　a　processing　block　and　an　interaction　block.　The　processing　block　mainly　utilizes　the　recurrent　layers　to　model　the　temporal　dynamics　of　the　enrollment　and　mixed　signal.　In　this　block,　the　speech　and　noise　signals　are　modeled　in　different　manners　and　the　similarity　between　the　enrollment　and　noise　can　be　reduced.　Afterwards,　the　processed　representations　of　the　enrollment　and　mixed　signal　are　utilized　to　derive　an　enhanced　representation　in　the　interaction　block.　This　enhanced　representation　emphasizes　the　active　speech　and　is　employed　as　an　auxiliary　guidance　for　the　extraction.　Experimental　results　demonstrate　the　effectiveness　of　our　proposed　method　in　complex　acoustic　environments.　©　2024　IEEE.