On the family of ML spectral estimates for mixed spectrum identification

Sherman, Peter; Lou, Kuiyang

doi:10.1109/78.80884

Cited by 35 publications

(18 citation statements)

References 22 publications

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“…The coefficients that are to be subsequently calculated via the least squares method will be found using the R(i)'s whose relation with the power spectra has already been established in Equation (21). In analogy, the expected correlation coefficients can be found using predicted power spectra using (27) This concludes that since the spectrum depends upon the autocorrelation; the window over which it is computed becomes immensely important.…”

Section: Inadequacy Of Lp Methods For Detection Of Whispered Speechmentioning

confidence: 99%

“…Hence it leads to poor characterization of the vocal tract transfer function. The MVDR spectra [21], on the other hand, is capable of modeling the power of the spectra efficiently at all harmonic frequencies due to the nature of the estimation method. The MVDR spectra also responds to increase in model order and improves the model at higher harmonic frequencies [22].…”

Section: Lp-mvdr Spectral Ratio Methods For Detection Of Whispered Speechmentioning

confidence: 99%

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Significance of parametric spectral ratio methods in detection and recognition of whispered speech

Mathur

Reddy

Hegde

2012

EURASIP J. Adv. Signal Process.

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In this article the significance of a new parametric spectral ratio method that can be used to detect whispered speech segments within normally phonated speech is described. Adaptation methods based on the maximum likelihood linear regression (MLLR) are then used to realize a mismatched train-test style speech recognition system. This proposed parametric spectral ratio method computes a ratio spectrum of the linear prediction (LP) and the minimum variance distortion-less response (MVDR) methods. The smoothed ratio spectrum is then used to detect whispered segments of speech within neutral speech segments effectively. The proposed LP-MVDR ratio method exhibits robustness at different SNRs as indicated by the whisper diarization experiments conducted on the CHAINS and the cell phone whispered speech corpus. The proposed method also performs reasonably better than the conventional methods for whisper detection. In order to integrate the proposed whisper detection method into a conventional speech recognition engine with minimal changes, adaptation methods based on the MLLR are used herein. The hidden Markov models corresponding to neutral mode speech are adapted to the whispered mode speech data in the whispered regions as detected by the proposed ratio method. The performance of this method is first evaluated on whispered speech data from the CHAINS corpus. The second set of experiments are conducted on the cell phone corpus of whispered speech. This corpus is collected using a set up that is used commercially for handling public transactions. The proposed whisper speech recognition system exhibits reasonably better performance when compared to several conventional methods. The results shown indicate the possibility of a whispered speech recognition system for cell phone based transactions.

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Section: Inadequacy Of Lp Methods For Detection Of Whispered Speechmentioning

confidence: 99%

Section: Lp-mvdr Spectral Ratio Methods For Detection Of Whispered Speechmentioning

confidence: 99%

Significance of parametric spectral ratio methods in detection and recognition of whispered speech

Mathur

Reddy

Hegde

2012

EURASIP J. Adv. Signal Process.

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“…This is not surprising since sinusoids have point mass. It is this same property that is responsible for the convergence of the th-order minimum variance (MV), denoted MV( ) spectrum at point frequency to the process power spectrum as [8], [13]. The MV( ) spectrum is defined to be the inverse of the sum of AR( ) spectra for .…”

Section: Theoremmentioning

confidence: 99%

Asymptotic statistical properties of AR spectral estimators for processes with mixed spectra

Lau

Sherman

White

2002

IEEE Trans. Inform. Theory

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Abstract-In this paper, the influence of a point spectrum on large sample statistics of the autoregressive (AR) spectral estimator is addressed. In particular, the asymptotic distributions of the AR coefficients, the innovations variance, and the spectral density estimator of a finite-order AR( ) model to a mixed spectrum process are presented. Various asymptotic results regarding AR modeling of a regular process with a continuous spectrum are arrived at as special cases of the results for the mixed spectrum setting. Finally, numerical simulations are performed to verify the analytical results.Index Terms-Asymptotic normality, autoregressive (AR) model, mixed spectrum processes, spectral analysis.

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“…The original work of [22] and [23] demonstrated this mechanism for the Minimum Variance estimate. Actually, the Minimum Variance estimate does not show clear advantage in the case of long data records as is commonplace in vibration analysis, and requires tremendous computational efforts.…”

Section: Approach Based On "Families Of Spectra"mentioning

confidence: 99%

New Separation Techniques for Output‐Only Modal Analysis

Antoni

Garibaldi

Marchesiello

et al. 2004

Shock and Vibration

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Caro Bruno, pensiamo sempre di vedere il tuo sorriso affacciato alla nostra porta, credendo di sentire i tuoi passi in corridoio: ci manchi.Abstract. The paper is devoted to the problem of discriminating between operational and natural modes of structures excited by generic inputs. This case often occurs when the system under analysis holds rotating parts and is contemporary excited by ambient noise; in this case the output-only techniques may fail being easily trapped in a misinterpretation of the system eigenvalues. A survey of the methods available in literature is given, together with the explanation of their failures. To solve this problem, two new techniques are introduced and their capabilities are checked with numerical and experimental data from a paper machine.

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On the family of ML spectral estimates for mixed spectrum identification

Cited by 35 publications

References 22 publications

Significance of parametric spectral ratio methods in detection and recognition of whispered speech

Significance of parametric spectral ratio methods in detection and recognition of whispered speech

Asymptotic statistical properties of AR spectral estimators for processes with mixed spectra

New Separation Techniques for Output‐Only Modal Analysis

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