Vocal effort detection based on ESN-RBF framework

Abstract：The frame based spectral feature cannot describe the inherent temporal correlation and dynamic change information in speech phenomena for vocal effort detection.In view of this, a vocal effort detection method based on ESN-RBF framework was proposed.The acoustic observation sequence was fed to an echo state network, and the reservoir of this echo state network was used to map the acoustic observation sequence to a vector in the high dimensional coding space.Then, RBF was employed to fit the probability density function of each VE mode by using the vectors in the high dimensional coding space.Finally, the minimum error rate Bayes decision was employed to judge the vocal effort mode.Experiments were conducted on test set with 5 000 isolated words, and the proposed method achieved 79.5% average recognition accuracy.The results showed that the proposed method could effectively obtain the correlation information between speech frames and overcome the defect of the independent hypothesis between frames.

Keyword：vocal effort detection;echo state network;reservoir;radial basis function;support vector machine;