A performance evaluation study of four wavelet algorithms for the pitch period estimation of speech signals

Obaidat, M. S.; Brodzik, A.; Sadoun, Balqies

doi:10.1016/s0020-0255(98)10032-4

Cited by 12 publications

(8 citation statements)

References 9 publications

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“…However, newer voice recognition applications allow a user to give commands fluently into the computer and these applications can recognize speech at up to 160 words per minute. Some applications are designed to recognize text and format it in order to allow continuous speech …”

Section: Traditional Biometric Technologiesmentioning

confidence: 99%

“…This customization allows the voice recognition to distinguish among humans' voice although each person speaks with different accent and inflection. Voice biometric features include physical characteristics such as vocal tracts, nasal cavities, mouth, and lips …”

Section: Traditional Biometric Technologiesmentioning

confidence: 99%

“…Obaidat et al devised a new scheme to identify speakers using four Wavelet algorithms with excellent accuracy.…”

Section: Traditional Biometric Technologiesmentioning

confidence: 99%

See 2 more Smart Citations

State of the art and perspectives on traditional and emerging biometrics: A survey

Traoré

Alshahrani

Obaidat

2018

Security and Privacy

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The last three decades have seen a shift and impressive progress in the biometric technologies landscape. Several major real‐world applications of biometrics have been released and are currently being used around the world. At the same time, several new biometrics modalities have emerged and have started making an impact in securing sensitive data, information, and systems. We present in this paper a survey of traditional and emerging biometrics by emphasizing their connection to human body parts, behavior, and cognition. A review of the state of the art in the key technologies is carried out along with a discussion of major applications currently available in the real world.

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Section: Traditional Biometric Technologiesmentioning

confidence: 99%

Section: Traditional Biometric Technologiesmentioning

confidence: 99%

See 1 more Smart Citation

State of the art and perspectives on traditional and emerging biometrics: A survey

Traoré

Alshahrani

Obaidat

2018

Security and Privacy

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“…The reference Fig. 4(e) was easily constructed after the pitch frequency of the speech signal was estimated [27,28]. Then, the fast ICA-R algorithm was used to analyze the noisy mixtures in Fig.…”

Section: Experiments With a Speech Signalmentioning

confidence: 99%

A fast algorithm for one-unit ICA-R

Lin

Zheng

Yin

et al. 2007

Information Sciences

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“…The positions with coincident maxima in different scales were recognized as GCIs. Emerging from the above concept, researchers had tried various kinds of WT to perform PD or GCI determination (Bing et al 2005;Chen and Wang 2002;Erçelebi 2003;Messaoud et al 2011;Obaidat et al 1998Obaidat et al , 1999.…”

Section: Introductionmentioning

confidence: 99%

Robust glottal closure instant detection by jointly exploiting stationary wavelet transform and harmonic superposition

Hsu

2015

Int J Speech Technol

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This study jointly utilizes stationary wavelet transform (SWT) and harmonic superposition (HS) techniques to locate zero-crossings closely related to glottal closure instants (GCI). The entire process is performed directly on voiced speech signals without referring to the linear prediction residual or voiced source signal derived by inverse filtering. Subsequent to the multi-scale SWT decomposition, a linear phase FIR filter is introduced to translate positive zero-crossings into pulse-like features. While the product across the approximation coefficients in various SWT levels sharpens impulse features, the HS is employed to sieve out the main pulses corresponding GCIs. The advantages of using the proposed SWT-HS scheme for GCI detection are examined using the PTDB-TUG database. Compared with the other two advanced methods, namely the SEDREAMS and ZFR, without the assistance of any refining process the proposed SWT-HS not only renders better accuracy in GCI positioning but exhibits superior robustness against additive noise.

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A performance evaluation study of four wavelet algorithms for the pitch period estimation of speech signals

Cited by 12 publications

References 9 publications

State of the art and perspectives on traditional and emerging biometrics: A survey

State of the art and perspectives on traditional and emerging biometrics: A survey

A fast algorithm for one-unit ICA-R

Robust glottal closure instant detection by jointly exploiting stationary wavelet transform and harmonic superposition

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