Robust Pitch Period Detection Using Dynamic

Das diesem Bericht zugrundeliegende Forschungsvorhaben wurde mit Mitteln des Bundesministers f ur Bildung, Wissenschaft, Forschung und Technologie unter dem F orderkennzeichen 01 IV 102 H/0 gef ordert. Die Verantwortung f ur den Inhalt dieser Arbeit liegt bei den Autoren. ABSTRACT In this paper, a new pitch synchronous F0-algorithm is described. The task of detecting pitch periods in the speech signal is solved with a search for an optimal path through a space of pitch period hypotheses. The search is eeciently implemented by dynamic programming (DP). The DP cost function is computed with an automatically trained artiicial neural network (ANN) which combines the outputs of heuristic functions measuring the similarity of adjacent period hypotheses. With this algorithm a coarse error rate of 4,75% on a German speech database is achieved. It outperforms the DPF0 algorithm, which itselfs outperforms two \conventional" algorithms.