In this paper, we present an approach to track the pitch of two simultaneous speakers. Using a well-known feature extraction method based on the correlogram, we track the resulting data using a factorial hidden Markov model (FHMM). In contrast to the recently developed multipitch determination algorithm , which is based on a HMM, we can accurately associate estimated pitch points with their corresponding source speakers. We evaluate our approach on the "Mocha-TIMIT" database  of speech utterances mixed at 0dB, and compare the results to the multipitch determination algorithm  used as a baseline. Experiments show that our FHMM tracker yields good performance for both pitch estimation and correct speaker assignment.
Bibliographic reference. Wohlmayr, Michael / Pernkopf, Franz (2008): "Multipitch tracking using a factorial hidden Markov model", In INTERSPEECH-2008, 147-150.