Evolutive HMM for multi-speaker tracking system

Seeking within a speech sequence the speaker utterances is one of the main tasks of indexing. In this paper, the proposed speaker tracking system is defined in the case where all speaker identities are known beforehand. The conversation is modeled as an evolutive HMM-like model, in which speaker models computed are added one by one. A temporary indexing is proposed after each speaker adding and then challenged at the next step. This process is iterated until all the speakers are detected. The system has been assessed using multi-speaker messages generated by concatenation of Switchboard mono-speaker segments. The obtained results show the potentiality of the proposed solution