Advancements in whisper-island detection using the linear predictive residual

In this study, we consider the use of a new entropy-based feature extracted from linear predictive residual for whisper-island detection within normally phonated audio streams. The proposed feature, which is sensitive to vocal effort changes between whisper and neutral speech, is integrated within a BIC/T²-BIC segmentation for vocal effort change point(VECP) detection and utilized for vocal effort classification. Evaluation is based on the proposed multi-error score(MES), where the improved feature is shown to improve performance in VECP detection with the lowest MES of 20.70. Furthermore, more accurate whisper-island detection was obtained using the proposed feature and algorithm. Finally, the experimental detection rate results of 97.37% represents the best whisper-island detection performance available in the literature to date.