Abstract
In this contribution, a method based on nonlinear prediction of speech signals is proposed for detecting the locations of the instances of glottal closures (GCI). For that purpose, feature signals are obtained from the nonlinear prediction of speech using a sliding window technique. The resulting feature signals show maxima caused by the glottal closures which can be utilized for the GCI detection. To assess the procedure, a speech database with corresponding EGG signals is analyzed providing GCIs as reference.
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Schnell, K. (2007). Estimation of Glottal Closure Instances from Speech Signals by Weighted Nonlinear Prediction. In: Chetouani, M., Hussain, A., Gas, B., Milgram, M., Zarader, JL. (eds) Advances in Nonlinear Speech Processing. NOLISP 2007. Lecture Notes in Computer Science(), vol 4885. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77347-4_19
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DOI: https://doi.org/10.1007/978-3-540-77347-4_19
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-77346-7
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