Two-channel speech analysis

Krishnamurthy, Ashok; Childers, D. G.

doi:10.1109/tassp.1986.1164909

Cited by 144 publications

(65 citation statements)

References 21 publications

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“…If, however, the closed phase is known, closed-phase covariance LPC can be beneficial by restricting its analysis window to the region in which the glottis is closed, i.e., . This circumvents the need for preemphasis and provides more accurate estimate of and therefore [5], [8], [10]. Consider the covariance of a finite segment of speech (10) in which no windowing function is applied to the speech signal.…”

Section: Closed-phase Covariance Lpcmentioning

confidence: 99%

“…1 shows a discontinuity at this instant in plots (a) and (b) but there is little evidence in the EGG signal of plots (c) and (d). The second definition of the GOI, defined in [8] and [37], is the maximum derivative of the EGG signal as marked with the line in Fig. 1.…”

Section: E Defining the Glottal Closed Phasementioning

confidence: 99%

“…In this work, we aim to find an analysis interval that is best-suited to closed-phase LPC analysis [5] that is shown not to always correspond to the closed phase estimated from the EGG signal. An automatic reference is proposed that builds upon earlier works in [5] and [8] by iteratively refining electroglottograph (EGG)-based estimates based upon the variance of the estimated voice source signal in the closed phase.…”

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confidence: 99%

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Estimation of Glottal Closing and Opening Instants in Voiced Speech Using the YAGA Algorithm

Thomas

Guðnason

Naylor

2012

IEEE Trans. Audio Speech Lang. Process.

109

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Abstract-Accurate estimation of glottal closing instants (GCIs) and opening instants (GOIs) is important for speech processing applications that benefit from glottal-synchronous processing including pitch tracking, prosodic speech modification, speech dereverberation, synthesis and study of pathological voice. We propose the Yet Another GCI/GOI Algorithm (YAGA) to detect GCIs from speech signals by employing multiscale analysis, the group delay function, and -best dynamic programming. A novel GOI detector based upon the consistency of the candidates' closed quotients relative to the estimated GCIs is also presented. Particular attention is paid to the precise definition of the glottal closed phase, which we define as the analysis interval that produces minimum deviation from an all-pole model of the speech signal with closedphase linear prediction (LP). A reference algorithm analyzing both electroglottograph (EGG) and speech signals is described for evaluation of the proposed speech-based algorithm. In addition to the development of a GCI/GOI detector, an important outcome of this work is in demonstrating that GOIs derived from the EGG signal are not necessarily well-suited to closed-phase LP analysis. Evaluation of YAGA against the APLAWD and SAM databases show that GCI identification rates of up to 99.3% can be achieved with an accuracy of 0.3 ms and GOI detection can be achieved equally reliably with an accuracy of 0.5 ms.Index Terms-Dynamic programming, electroglottograph (EGG), glottal closing instants (GCIs), glottal opening instants (GOIs), group delay function, multiscale analysis, speech processing.

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Section: Closed-phase Covariance Lpcmentioning

confidence: 99%

Section: E Defining the Glottal Closed Phasementioning

confidence: 99%

mentioning

confidence: 99%

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Estimation of Glottal Closing and Opening Instants in Voiced Speech Using the YAGA Algorithm

Thomas

Guðnason

Naylor

2012

IEEE Trans. Audio Speech Lang. Process.

109

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“…The supplied current is different for each particular device, but is not stronger than several milliamperes. The voltage between the electrodes depends on the tissue impedance [1][2][3]. The power dissipation of only several microwatts occurs at the level the subject's vocal folds.…”

Section: Fig 1 Instrumentation For Eggmentioning

confidence: 99%

Egg Signal Classification Using Principal Component Analysis

Nayak¹,

Puttamadappa²

2009

Int. Jour. Intel. Elec. Sys.

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The method is used to register the laryngeal behavior indirectly by measuring change in the electrical impedance across the throat during speak or voice. In this Electroglottography (EGG) signal acquisition, the electrodes are made of steel. They have the form of rectangles covering an area of 10.75 cm2. It is designed as a ring electrode encircling each of the two other electrodes. The electrodes are mounted on a flexible band whose length is adjusted to hold the electrodes in a steady position and to still allow the subject to comfortably speak and breathe naturally. The electrodes are mounted on a small holder which is pressed against the throat by hand. A signal generator supplies an AC sinusoidal current usually ranging from 2 MHz. The RF carrier signal is amplitude modulated by the modulating speech/ voice signal and the demodulated signal is extracted. The variations in the signal correspond to the vocal fold abduction/laryngeal movement. For normal and pathology conditions, the results are recorded. These values form a feature vector, which reveals information regarding pathology. Principal Component Analysis technique (PCA) is used for classification, giving successful results for the specific data set considered.

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“…However, this blind deconvolution relies on accurate segmentation of the voiced speech larynx cycle into closed and open phases of the glottis. To date, this has required the use of contemporaneous laryngographic recordings [3,4] (EGG) from which to derive glottal closure instants. Because the EGG signal is not normally available in practical applications, there exists a strong motivation to develop techniques for extracting GCIs from the speech signal alone.…”

Section: Introductionmentioning

confidence: 99%

The DYPSA algorithm for estimation of glottal closure instants in voiced speech

Kounoudes¹,

Naylor²,

Brookes³

2002

IEEE International Conference on Acoustics Speech and Signal Processing

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We present the DYPSA algorithm for automatic and reliable estimation of glottal closure instants (GCIs) in voiced speech. Reliable GCI estimation is essential for closed-phase speech analysis, from which can be derived features of the vocal tract and, separately, the voice source. It has been shown that such features can be used with significant advantages in applications such as speaker recognition. DYPSA is automatic and operates using the speech signal alone without the need for an EGG or Laryngograph signal. It incorporates a new technique for estimating GCI candidates and employs dynamic programming to select the most likely candidates according to a defined cost function. We review and evaluate three existing methods and compare our new algorithm to them. Results for DYPSA show GCI detection accuracy to within ±0.25ms on 87% of the test database and fewer than 1% false alarms and misses.

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Two-channel speech analysis

Cited by 144 publications

References 21 publications

Estimation of Glottal Closing and Opening Instants in Voiced Speech Using the YAGA Algorithm

Estimation of Glottal Closing and Opening Instants in Voiced Speech Using the YAGA Algorithm

Egg Signal Classification Using Principal Component Analysis

The DYPSA algorithm for estimation of glottal closure instants in voiced speech

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