We introduce an EM algorithm for automatic speaker gain adaptation, and use this approach for probabilistic multipitch tracking. We derive a lower bound on the log-likelihood of the gain parameters and use a fast pruning method to make lower bound optimization efficient. We evaluate the performance of gain adapted multipitch tracking on the GRID database, where 3000 speech mixtures were generated for each mixing level. For gain differences in the range of zero up to 18dB, the proposed method achieves almost the same performance as for the case where the gain is assumed to be known.
Bibliographic reference. Wohlmayr, Michael / Pernkopf, Franz (2011): "EM-based gain adaptation for probabilistic multipitch tracking", In INTERSPEECH-2011, 1969-1972.