Prosodic feature generation for back-channel prediction
Thamar Solorio, Olac Fuentes, Nigel Ward, Yaffa Al Bayyari · 2006
Using prosodic information to predict when back-channels are appropriate in spontaneous dialogs has become somewhat of a reference problem for automatic discovery techniques. Here we present experiments with two ideas: the use of features derived from randomly generated pitch and energy filters, and the use of instancebased learning, specifically the Locally Weighted Linear Regression (LWLR) algorithm. For the task of predicting possible backchannel locations in Iraqi Arabic [6], we obtain 22 % precision and 51 % recall, which is as good as that obtained using a laboriously developed and hand-tuned rule. 1.