Evaluation of the pitch estimation algorithms in the monopitch and multipich cases

Abstract : Reliably tracking the fundamental frequency F0 of the components is an important step in the separation of superimposed speech signals. Several Pitch Estimation Algorithms (PEAs) are potentially usable and a rigorous evaluation method is needed. However, even in the monopitch case, many variations between them render such a comparison difficult. The F0min-F0max interval extent, the use of a priori information on the whole sequence or database and above all the arbitrary voicing threshold setting lead to 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 voicing according to the coincidence between the voiced and unvoiced parts of both signals. This problem is treated by defining a metric linking the PEAS’s hypotheses to the pitch values of the isolated signals. The proposed methodology is applied to several PEAs on several databases in the monopitch case.
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https://hal.archives-ouvertes.fr/hal-01836485
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Submitted on : Tuesday, November 20, 2018 - 10:41:10 AM
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François Signol, Claude Barras, Jean-Sylvain Liénard. Evaluation of the pitch estimation algorithms in the monopitch and multipich cases. Acoustics'08, Acoustical Society of America, Jun 2008, Paris, France. ⟨hal-01836485⟩

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