Correcting the use of ensemble averages in the calculation of harmonics to noise ratios in voice signals

Ferrer, Carlos A.; González, Eduardo; Hernández-Dıaz, Marıa E.

doi:10.1121/1.1940450

Cited by 6 publications

(19 citation statements)

References 9 publications

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“…This representation has been used for source [3] and radiated signals [5,9,14,16] as well as for both indistinctly [12,15]. If we denote the glottal flow waveform as g(t), the vocal tract impulse response as h(t), the radiation at lips as r(t), and the turbulent noise generated at the glottis as n(t), the components of the pulse waveform in (1) can be expressed differently for the source and radiated signals.…”

Section: Ensemble-averages Hnr Calculationmentioning

confidence: 99%

“…In [12] the need of averaging a large number of pulses is suppressed, by determining an expression which corrects the ensemble-average HNR.…”

mentioning

confidence: 99%

“…In this paper, an analysis on the original ensemble average HNR formula in the presence of shimmer is performed, which results in a general form of Ferrer's correcting formula [12] and allows the suppression of the effect of shimmer in HNR.…”

mentioning

confidence: 99%

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Removing the Influence of Shimmer in the Calculation of Harmonics-To-Noise Ratios Using Ensemble-Averages in Voice Signals

Ferrer

González

Hernández-Dıaz

et al. 2009

EURASIP J. Adv. Signal Process.

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Recommended by Juan I. Godino-LlorenteHarmonics-to-noise ratios (HNRs) are affected by general aperiodicity in voiced speech signals. To specifically reflect a signal-toadditive-noise ratio, the measurement should be insensitive to other periodicity perturbations, like jitter, shimmer, and waveform variability. The ensemble averaging technique is a time-domain method which has been gradually refined in terms of its sensitivity to jitter and waveform variability and required number of pulses. In this paper, shimmer is introduced in the model of the ensemble average, and a formula is derived which allows the reduction of shimmer effects in HNR calculation. The validity of the technique is evaluated using synthetically shimmered signals, and the prerequisites (glottal pulse positions and amplitudes) are obtained by means of fully automated methods. The results demonstrate the feasibility and usefulness of the correction.

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Section: Ensemble-averages Hnr Calculationmentioning

confidence: 99%

“…In [12] the need of averaging a large number of pulses is suppressed, by determining an expression which corrects the ensemble-average HNR.…”

mentioning

confidence: 99%

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Removing the Influence of Shimmer in the Calculation of Harmonics-To-Noise Ratios Using Ensemble-Averages in Voice Signals

Ferrer

González

Hernández-Dıaz

et al. 2009

EURASIP J. Adv. Signal Process.

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“…That is the case of evoked potentials, which are waveforms emitted by the brain as response to certain optical, acoustical, or electrical stimulation [1]. Many other bioelectric signals, such as ventricular late potentials [3], [4], and the voice [5] can be also classified as ERP in a wide sense (ERPWS).…”

Section: Introductionmentioning

confidence: 99%

“…The most commonly used method to enhance the signal of interest to detect or estimate the ERPWS is the coherent averaging [3], [5]. This technique averages a number of epochs, N, using temporal references or fiducial marks, /w, (0 < / < TV), and analysis windows of length a.…”

Section: Introductionmentioning

confidence: 99%

Simulation of Event-Related Potentials in a Wide Sense for Assessment of Detection∕Estimation Algorithms

Taboada‐Crispi¹,

Orozco‐Monteagudo²,

Ferrer³

et al. 2008

AIP Conference Proceedings

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Event-related potentials in a wide sense (ERPWS) are bioelectric signals that appear associated to certain stimuli or event. The most common way to detect and estimate ERPWS is based on coherent averaging, but alternative techniques have been proposed to overcome certain limitations of the former. A flexible and realistic simulator is designed here to assess, in a controlled scenario, algorithms used to detect/estimate ERPWS. The system generates signals resembling real-world ERPWS, by adjusting waveforms, jitter, width and amplitude modulation, sampling/quantization effects, noise and interference. Having these simulated records, we can apply the algorithm under assessment, and easily estimate parameters as the variance and the bias of the remnant noise, as well as the signal-tonoise ratio. With those parameters as a reference, algorithms to detect/estimate ERPWS can be objectively compared.

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Evaluation of Time and Frequency Domain-Based Methods for the Estimation of Harmonics-to-Noise-Ratios in Voice Signals

Ferrer

González

Hernández-Dıaz

2006

Lecture Notes in Computer Science

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In this paper several approaches of time and frequency domain-based algorithms to estimate harmonics-to-noise ratios (HNR) in voice signals are compared. The approaches covered incorporate a recent time-domain correction to a classic method, as well as a frequency-domain adjustment introduced here. The experimental comparisons include the number of pitch periods needed to obtain the best HNR estimates, as well as the sensitivity of the methods to different perturbations of the periodicity pattern, like shimmer, jitter, noise and combinations of them. Time domain methods show better performance than frequency-based approaches, and moreover, the correction to the ensembleaverage time domain technique reduces the required number of pulses by an order of magnitude.

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Correcting the use of ensemble averages in the calculation of harmonics to noise ratios in voice signals

Cited by 6 publications

References 9 publications

Removing the Influence of Shimmer in the Calculation of Harmonics-To-Noise Ratios Using Ensemble-Averages in Voice Signals

Removing the Influence of Shimmer in the Calculation of Harmonics-To-Noise Ratios Using Ensemble-Averages in Voice Signals

Simulation of Event-Related Potentials in a Wide Sense for Assessment of Detection∕Estimation Algorithms

Evaluation of Time and Frequency Domain-Based Methods for the Estimation of Harmonics-to-Noise-Ratios in Voice Signals

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