Evaluation of the pitch estimation algorithms in the monopitch and multipich cases
Résumé
Reliably tracking the fundamental frequency F0 of the components is an important step in the separation ofsuperimposed speech signals. Several Pitch Estimation Algorithms (PEAs) are potentially usable and a rigorousevaluation method is needed. However, even in the monopitch case, many variations between them render such acomparison difficult. The F0min-F0max interval extent, the use of a priori information on the whole sequence ordatabase and above all the arbitrary voicing threshold setting lead to large differences in the results. These biasescan be removed by setting the F0 bounds to fixed values acceptable for many voices, by proceeding with theevaluation on a strictly frame-to-frame basis, and by fixing the voicing threshold in order to get an equal errorrate for overvoiced and undervoiced frames. In the multipitch case any frame may exhibit 0, 1 or 2 valid voicingaccording to the coincidence between the voiced and unvoiced parts of both signals. This problem is treated bydefining a metric linking the PEAS’s hypotheses to the pitch values of the isolated signals. The proposedmethodology is applied to several PEAs on several databases in the monopitch case.
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