Abstract
Weighted Correlation based Atom Decomposition (WCAD) algorithm is a technique for intonation modelling that uses a matching pursuit framework to decompose the F0 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 F0. 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).
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Notes
- 1.
The WCAD implementation code is available on gitHub at https://github.com/dipteam/wcad.
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Acknowledgments
This work was supported by the Hungarian National Innovation Office (OTKA-PD-112598, “Automatic Phonological Phrase and Prosodic Event Detection for the Extraction of Syntactic and Semantic/Pragmatic Information from Speech” and by the Swiss National Science Foundation (No. CRSII2-147611/1, “SP2: SCOPES Project on Speech Prosody”).
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Szaszák, G., Tündik, M.Á., Gerazov, B., Gjoreski, A. (2016). Combining Atom Decomposition of the F0 Track and HMM-based Phonological Phrase Modelling for Robust Stress Detection in Speech. In: Ronzhin, A., Potapova, R., Németh, G. (eds) Speech and Computer. SPECOM 2016. Lecture Notes in Computer Science(), vol 9811. Springer, Cham. https://doi.org/10.1007/978-3-319-43958-7_19
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