This paper describes the exploration of text-independent speaker identification using novel approaches based on speakersÂ’ phonetic features instead of traditional acoustic features. Different phonetic speaker identification approaches are discussed in this paper and evaluated using two speaker identification systems: one multilingual system and one single language multiple-engine system. Furthermore, text-independent speaker identification experiments are carried out on a distant-microphone database as well as gender identifi- cation experiments are investigated on the NIST 1999 Speaker Recognition Evaluation dataset. The results show that phonetic features are powerful for speaker identification and gender identification.