Alex del Giudice1, Ryan K. Shosted2, Katherine Davidson1, Mohammad Salihie1 & Amalia Arvaniti1
1University of California, San Diego; 2University of Illinois at Urbana-Champaign

ID 1283
[full paper]

The labeling of “elbows” in an F0 contour is considered an enterprise beset with difficulty due to the inability of humans to locate pitch elbows with accuracy, consistency and in a manner devoid of theoretical bias. This paper investigates the extent to which human labelers can agree with one another in locating elbows and how they fare by comparison to four algorithms. The results show that humans are more consistent than has been suggested and that the algorithm that best approximates their intuition is the least-squares fitting algorithm. The success of algorithmic elbow location, however, depends on the selection of the contour stretch in which the elbow is to be located; This selection is most consistent if performed by a theoretically informed human annotator, strongly suggesting that a completely a-theoretical annotation of F0 contours may be impossible to achieve, and ultimately undesirable.