Combining Atom Decomposition of the FO Track and HMM-based Phonological Phrase Modelling for Robust Stress Detection in Speech

摘要

Weighted Correlation based Atom Decomposition (WCAD) algorithm is a technique for intonation modelling that uses a matching pursuit framework to decompose the FO contour into a set of basic components, called atoms. The atoms attempt to model the physiological activation of the laryngeal muscles responsible for changes in FO. Recently, WCAD has been upgraded to use the orthogonal matching pursuit (OMP) algorithm, which gives qualitative improvements in the modelling of intonation. A possible exploitation of the OMP based WCAD is the automatic detection of stress in speech, which we undertake for the Hungarian language. Correlation is demonstrated between stress and atomic peaks, as well as between stress and atomic valleys on the previous syllable. The stress detection technique based on WCAD is compared to a baseline system using HMM/GMM stress/phrase models. 7 % improvement is noticed in the F-measure compared to baseline when evaluating on hand-made reference. Finally, we propose a hybrid approach which outperforms both individual systems (by 11 % compared to the baseline).