Automatic glottal inverse filtering from speech and electroglottographic signals

Veeneman, D.; BeMent, Spencer L.

doi:10.1109/tassp.1985.1164544

Cited by 74 publications

(44 citation statements)

References 14 publications

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“…Hence, the speech signal in the closed phase region represents the free resonances of the supralaryngeal vocal-tract system. Analysis of the speech signal in the closed phase regions provides an accurate estimate of the frequency response of the supralaryngeal vocal-tract system [1], [2]. With the knowledge of the epochs, it is possible to determine the characteristics of the voice source by a careful analysis of the signal within a glottal pulse.…”

Section: A Significance Of Epochs In Speech Analysismentioning

confidence: 99%

Epoch Extraction From Speech Signals

Murty

Yegnanarayana

2008

IEEE Trans. Audio Speech Lang. Process.

560

288

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Abstract-Epoch is the instant of significant excitation of the vocal-tract system during production of speech. For most voiced speech, the most significant excitation takes place around the instant of glottal closure. Extraction of epochs from speech is a challenging task due to time-varying characteristics of the source and the system. Most epoch extraction methods attempt to remove the characteristics of the vocal-tract system, in order to emphasize the excitation characteristics in the residual. The performance of such methods depends critically on our ability to model the system. In this paper, we propose a method for epoch extraction which does not depend critically on characteristics of the time-varying vocaltract system. The method exploits the nature of impulse-like excitation. The proposed zero resonance frequency filter output brings out the epoch locations with high accuracy and reliability. The performance of the method is demonstrated using CMU-Arctic database using the epoch information from the electro-glottograph as reference. The proposed method performs significantly better than the other methods currently available for epoch extraction. The interesting part of the results is that the epoch extraction by the proposed method seems to be robust against degradations like white noise, babble, high-frequency channel, and vehicle noise.

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Section: A Significance Of Epochs In Speech Analysismentioning

confidence: 99%

Epoch Extraction From Speech Signals

Murty

Yegnanarayana

2008

IEEE Trans. Audio Speech Lang. Process.

560

288

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“…The elements of the cost vector evaluated for the th GCI of subset (10) all lie in the range [ 0.5,0.5] and are defined below. We additionally define , and to be the sample indices of GCI candidates , and respectively where, for clarity of notation, we omit the explicit dependency of on .…”

Section: Dynamic Programmingmentioning

confidence: 99%

“…For example, it has been shown [5], [6] that excitation features can be used to improve discrimination between speakers in a speaker recognition task. Using the techniques of glottal inverse filtering [7]- [9], the voice source signal can be estimated by deconvolving the speech signal with the all-zero filter obtained from closed-phase LPC for both normal and pathological speech [10]. In this approach, least squares estimates are made of the parameters of an all-pole model of the speech signal using covariance LPC applied only to those samples of the speech signal that occur at times when the glottis is closed.…”

Section: Introductionmentioning

confidence: 99%

Estimation of Glottal Closure Instants in Voiced Speech Using the DYPSA Algorithm

Naylor

Kounoudes

Guðnason

et al. 2007

IEEE Trans. Audio Speech Lang. Process.

289

218

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Abstract-We present the Dynamic Programming Projected Phase-Slope Algorithm (DYPSA) for automatic estimation of glottal closure instants (GCIs) in voiced speech. Accurate estimation of GCIs is an important tool that can be applied to a wide range of speech processing tasks including speech analysis, synthesis and coding. DYPSA is automatic and operates using the speech signal alone without the need for an EGG signal. The algorithm employs the phase-slope function and a novel phase-slope projection technique for estimating GCI candidates from the speech signal. The most likely candidates are then selected using a dynamic programming technique to minimize a cost function that we define. We review and evaluate three existing methods of GCI estimation and compare the new DYPSA algorithm to them. Results are presented for the APLAWD and SAM databases for which 95.7% and 93.1% of GCIs are correctly identified.

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“…However, since the larynx cannot be separated from the vocal tract, the actual voice source cannot be measured; instead, it has to be estimated. Such estimation can be based on the voice pressure wave measured at the output of the lips (voice wave) [2], on measurements of mouth airflow volume velocity [3] or on combining information obtained from the voice wave and from other signals, such as the electroglottogram [4].…”

Section: Introductionmentioning

confidence: 99%

Analysis of Measured and Simulated Supraglottal Acoustic Waves

et al. 2016

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To date, while much attention has been paid to the estimation and modelling of the voice source (i.e. the glottal airflow volume velocity), the measurement and characterisation of the supraglottal pressure wave have been much less studied. Some previous results have unveiled that the supraglottal pressure wave has some spectral resonances similar to those of the voice pressure wave. This makes the supraglottal wave partially intelligible. While the explanation for such effect seems to be clearly related to the reflected pressure wave travelling upstream along the vocal tract, the influence that non-linear source-filter interaction has on it is not as clear. This paper provides an insight into this issue by comparing the acoustic analyses of measured and simulated supraglottal and voice waves. Simulations have been performed using a high-dimensional discrete vocal-fold model. Results of such comparative analysis indicate that spectral resonances in the supraglottal wave are mainly caused by the regressive pressure wave that travels upstream along the vocal tract and not by source-tract interaction. On the contrary and according to simulation results, source-tract interaction has a role in the loss of intelligibility that happens in the supraglottal wave with respect to the voice wave. This loss of intelligibility mainly corresponds to spectral differences around the frequency of the second formant.

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Automatic glottal inverse filtering from speech and electroglottographic signals

Cited by 74 publications

References 14 publications

Epoch Extraction From Speech Signals

Epoch Extraction From Speech Signals

Estimation of Glottal Closure Instants in Voiced Speech Using the DYPSA Algorithm

Analysis of Measured and Simulated Supraglottal Acoustic Waves

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