Evaluation of the Pitch Estimation Algorithms in the monopitch and multipitch cases
François Signol, Claude Barras, Jean-Sylvain Liénard · The Journal of the Acoustical Society of America · 2008
Reliably tracking the fundamental frequency F0 of the components is an important step in the separation of superimposed speech signals. Several Pitch Estimation Algorithms are potentially usable and a rigorous evaluation method is needed in order to compare them. However, even in the monopitch case, many variations between them render such a comparison difficult. The extent of the F0min-F0max interval, the use of a priori information on the whole sequence or database, and above all the arbitrary setting of the voicing threshold, yield large differences in the results. These biases can be removed by setting the F0 bounds to fixed values acceptable for many voices, by proceeding with the evaluation on a strictly frame-to-frame basis, and by fixing the voicing threshold in order to get an equal error rate for overvoiced and undervoiced frames. In the multipitch case any frame may exhibit 0, 1, or 2 valid voicings according to the coincidence between the voiced and unvoiced parts of both signals. This problem is treated by defining a similarity measure linking the PEA's hypotheses to the pitch values of the isolated signals. The proposed methodology is applied to several PEAs, using the Keele database in monopitch and multipich setups.