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Pitch marking is a major task in speech processing. Thus, an accurate detection of pitch marks (PM) is required. In this paper, we propose a hybrid method for pitch marking that combines outputs of two different speech signal based pitch marking algorithms (PMA). We use a finite state machine (FSM) to represent and combine the pitch marks. The hybrid PMA is implemented in four stages: preprocessing, alignment, selection and postprocessing. In the alignment stage, the preprocessed pitch marks are shifted to a local minimum of the speech signal and the confidence score for every pitch mark is calculated. The confidence scores are used as transition weights for the FSM. The PMA outputs are combined into a single sequence of pitch marks. The more accurate pitch marks with the highest confidence score are chosen in the selection stage. A PM reference database contains 10 minutes speech including manually adjusted PM. The evaluation results indicate that the proposed hybrid method outperforms the single PMAs but also other current state-of-the-art algorithms which have been evaluated on a second reference database containing 44 speakers.