A method and system for is disclosed for cross-lingual voice conversion. A speech-to-speech system may include hidden Markov model (HMM) HMM based speech modeling for both recognizing input speech and synthesizing output speech. A cross-lingual HMM may be initially set to an output HMM trained with a voice of an output speaker in an output language. An auxiliary HMM may be trained with a voice of an auxiliary speaker in an input language. A matching procedure, carried out under a transform that compensates for speaker differences, may be used to match each HMM state of the output HMM to a HMM state of the auxiliary HMM. The HMM states of the cross-lingual HMM may be replaced with the matched states. Transforms may be applied to adapt the cross-lingual HMM to the voices of the auxiliary speaker and of an input speaker. The cross-lingual HMM may be used for speech synthesis.