Detection of the Glottal Closure Instants Using Empirical Mode Decomposition

This work explores the effectiveness of the Intrinsic Mode Functions (IMFs) of the speech signal, in estimating its Glottal Closure Instants (GCIs). The IMFs of the speech signal, which are its AM–FM or oscillatory components, are obtained from two similar nonlinear and non-stationary signal analysi...

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Detalles Bibliográficos
Autores: Sharma, A. Surja, Prasanna, S. R. M., Rufiner, Hugo Leonardo, Schlotthauer, Gaston
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2017
País:Argentina
Institución:Consejo Nacional de Investigaciones Científicas y Técnicas
Repositorio:CONICET Digital (CONICET)
Idioma:inglés
OAI Identifier:oai:ri.conicet.gov.ar:11336/41422
Acceso en línea:http://hdl.handle.net/11336/41422
Access Level:acceso abierto
Palabra clave:Glottal Closure Instants
Empirical Mode Decomposition
Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise
Modified Empirical Mode Decomposition
Intrinsic Mode Functions
https://purl.org/becyt/ford/2.2
https://purl.org/becyt/ford/2
Descripción
Sumario:This work explores the effectiveness of the Intrinsic Mode Functions (IMFs) of the speech signal, in estimating its Glottal Closure Instants (GCIs). The IMFs of the speech signal, which are its AM–FM or oscillatory components, are obtained from two similar nonlinear and non-stationary signal analysis techniques—Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (ICEEMDAN), and Modified Empirical Mode Decomposition (MEMD). Both these techniques are advanced variants of the original technique—Empirical Mode Decomposition (EMD). MEMD is much faster than ICEEMDAN, whereas the latter curtails mode-mixing (a drawback of EMD) more effectively. It is observed that the partial summation of a certain subset of the IMFs results in a signal whose minima are aligned with the GCIs. Based on this observation, two different methods are devised for estimating the GCIs from the IMFs of ICEEMDAN and MEMD. The two methods are captioned ICEEMDAN-based GCIs Estimation (IGE) and MEMD-based GCIs Estimation (MGE). The results reveal that IGE and MGE provide consistent and reliable estimates of the GCIs, compared to the state-of-the-art methods, across different scenarios—clean, noisy, and telephone channel conditions.