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Chao-chin Yang - One of the best experts on this subject based on the ideXlab platform.

  • wavelength division multiplexing Spectral Amplitude coding applications in fiber vibration sensor systems
    IEEE Sensors Journal, 2011
    Co-Authors: Hsu-chih Cheng, Chao-chin Yang, Chung-hao Wu, Yao-tang Chang
    Abstract:

    This paper presents a wavelength division multiplexing/Spectral Amplitude coding system with optical code-division multiple-access, for applications using fiber vibration sensors. The device makes use of fiber Bragg grating (FBG) etching on optical fibers to provide encoding/decoding functionality. According to the orthogonal properties of Spectral Amplitude coding (SAC) using m-sequence code, the encoding- decoding devices that employ FBG filters provide a considerable reduction in multiple access interference in optical code division multiple access systems. The proposed fiber vibration sensor located between the encoder and optical circulator enables the measurement of multiple points. Experimental results reveal that the proposed sensor detects a variety of vibrational signals.

  • Wavelength Division Multiplexing/Spectral Amplitude Coding Applications in Fiber Vibration Sensor Systems
    IEEE Sensors Journal, 2011
    Co-Authors: Hsu-chih Cheng, Chao-chin Yang, Chung-hao Wu, Yao-tang Chang
    Abstract:

    This paper presents a wavelength division multiplexing/Spectral Amplitude coding system with optical code-division multiple-access, for applications using fiber vibration sensors. The device makes use of fiber Bragg grating (FBG) etching on optical fibers to provide encoding/decoding functionality. According to the orthogonal properties of Spectral Amplitude coding (SAC) using m-sequence code, the encoding- decoding devices that employ FBG filters provide a considerable reduction in multiple access interference in optical code division multiple access systems. The proposed fiber vibration sensor located between the encoder and optical circulator enables the measurement of multiple points. Experimental results reveal that the proposed sensor detects a variety of vibrational signals.

  • Spectral Amplitude Coding Optical CDMA Networks Using Waveguide Gratings
    2010
    Co-Authors: Chao-chin Yang
    Abstract:

    One new code family for Spectral Amplitude coding optical code-division multiple-access is proposed. Due to the cyclic property of the proposed code, one arrayed waveguide grating (AWG) can be used to generate all the codewords in one code. Since can be an even number such as eight, commercial AWGs can be used for coder implementation. Index Terms—Arrayed waveguide grating (AWG), Bose differ- ence set (BDS), optical code-division multiple-access (OCDMA), Spectral Amplitude coding (SAC).

  • Spectral Amplitude Coding Optical CDMA Networks Using $2^{m}\times 2^{m}$ Waveguide Gratings
    IEEE Photonics Technology Letters, 2010
    Co-Authors: Chao-chin Yang
    Abstract:

    One new code family for Spectral Amplitude coding optical code-division multiple-access is proposed. Due to the cyclic property of the proposed code, one arrayed waveguide grating (AWG) can be used to generate all the codewords in one code. Since can be an even number such as eight, commercial AWGs can be used for coder implementation.

  • hybrid wavelength division multiplexing Spectral Amplitude coding optical cdma system
    IEEE Photonics Technology Letters, 2005
    Co-Authors: Chao-chin Yang
    Abstract:

    One Spectral-Amplitude-coding (SAC) scheme combined with wavelength-division-multiplexing (WDM) is proposed for optical code-division multiple-access systems. The supported code length is more flexible than the previous SAC codes and the corresponding encoder-decoder requires less fiber gratings, thus, the system becomes cheap and simple. As compared to the conventional SAC systems, this WDM/SAC system not only reserves the interference-cancellation property, but also has better performance against the effect of the phase-induced intensity noise arising in the photodetecting process. Thus, a larger number of active users can be supported under a given bit-error rate.

Michael T Johnson - One of the best experts on this subject based on the ideXlab platform.

  • distributed multichannel speech enhancement with minimum mean square error short time Spectral Amplitude log Spectral Amplitude and Spectral phase estimation
    Signal Processing, 2012
    Co-Authors: Marek B. Trawicki, Michael T Johnson
    Abstract:

    In this paper, the authors present optimal multichannel frequency domain estimators for minimum mean-square error (MMSE) short-time Spectral Amplitude (STSA), log-Spectral Amplitude (LSA), and Spectral phase estimation in a widely distributed microphone configuration. The estimators utilize Rayleigh and Gaussian statistical models for the speech prior and noise likelihood with a diffuse noise field for the surrounding environment. Based on the Signal-to-Noise Ratio (SNR) and Segmental Signal-to-Noise Ratio (SSNR) along with the Log-Likelihood Ratio (LLR) and Perceptual Evaluation of Speech Quality (PESQ) as objective metrics, the multichannel LSA estimator decreases background noise and speech distortion and increases speech quality compared to the baseline single channel STSA and LSA estimators, where the optimal multichannel Spectral phase estimator serves as a significant quantity to the improvements, and demonstrates robustness due to time alignment and attenuation factor estimation. Overall, the optimal distributed microphone Spectral estimators show strong results in noisy environments with application to many consumer, industrial, and military products.

  • Distributed multichannel speech enhancement with minimum mean-square error short-time Spectral Amplitude, log-Spectral Amplitude, and Spectral phase estimation
    Signal Processing, 2012
    Co-Authors: Marek B. Trawicki, Michael T Johnson
    Abstract:

    In this paper, the authors present optimal multichannel frequency domain estimators for minimum mean-square error (MMSE) short-time Spectral Amplitude (STSA), log-Spectral Amplitude (LSA), and Spectral phase estimation in a widely distributed microphone configuration. The estimators utilize Rayleigh and Gaussian statistical models for the speech prior and noise likelihood with a diffuse noise field for the surrounding environment. Based on the Signal-to-Noise Ratio (SNR) and Segmental Signal-to-Noise Ratio (SSNR) along with the Log-Likelihood Ratio (LLR) and Perceptual Evaluation of Speech Quality (PESQ) as objective metrics, the multichannel LSA estimator decreases background noise and speech distortion and increases speech quality compared to the baseline single channel STSA and LSA estimators, where the optimal multichannel Spectral phase estimator serves as a significant quantity to the improvements, and demonstrates robustness due to time alignment and attenuation factor estimation. Overall, the optimal distributed microphone Spectral estimators show strong results in noisy environments with application to many consumer, industrial, and military products. © 2011 Elsevier B.V. All Rights Reserved.

  • INTERSPEECH - Improvements of the Beta-Order Minimum Mean-Square Error (MMSE) Spectral Amplitude Estimator using Chi Priors
    2012
    Co-Authors: Marek B. Trawicki, Michael T Johnson
    Abstract:

    In this paper, the authors propose the Beta-Order Minimum Mean-Square Error (MMSE) Spectral Amplitude estimator with Chi statistical models for the speech priors. The new estimator incorporates both a shape parameter on the distribution and cost function parameter. The performance of the MMSE Beta-Order Spectral Amplitude estimator with Chi speech prior is evaluated using the Segmental Signal-to-Noise Ratio (SSNR) and Perceptual Evaluation of Speech Quality (PESQ) objective quality measures. From the experimental results, the new estimator provides gains of 0-3 dB and 0-0.3 in SSNR and PESQ improvements over the corresponding MMSE Beta-Order MMSE Spectral Amplitude estimator with the standard Rayleigh statistical models for the speech prior.

Sophie Larochelle - One of the best experts on this subject based on the ideXlab platform.

Benoit Champagne - One of the best experts on this subject based on the ideXlab platform.

  • Microphone array based speech Spectral Amplitude estimators with phase estimation
    2014 IEEE International Symposium on Circuits and Systems (ISCAS), 2014
    Co-Authors: Mahdi Parchami, Benoit Champagne
    Abstract:

    Bayesian estimators of short time Spectral Amplitude (STSA) have received considerable attention in the field of speech enhancement. In this paper, we propose new multi-microphone extensions for the conventional Ephraim and Malah's speech Spectral Amplitude estimation method. Unlike the conventional estimators where the Spectral phase is assumed to be uniformly distributed, the proposed extensions treat the latter as an unknown parameter to be estimated. It is shown that the proposed methods can exploit Spectral phase estimates to improve the performance of the current speech STSA estimators and have the potential to provide even further improvement given a more accurate estimate of the Spectral phase. Experimental results indicate the superiority of the new approaches in terms of noise reduction and speech distortion measures, in addition to the reduced computational complexity provided by the proposed minimum mean square method as compared to state-of-the-art solutions.

  • Bayesian Spectral Amplitude estimation for speech enhancement with correlated Spectral components
    2009 IEEE SP 15th Workshop on Statistical Signal Processing, 2009
    Co-Authors: Eric Plourde, Benoit Champagne
    Abstract:

    In Bayesian short-time Spectral Amplitude (STSA) estimation for single channel speech enhancement, the Spectral components are traditionally assumed to be uncorrelated. However, this assumption is not exact since some correlation is present in practice. In this paper, we propose a STSA estimator with correlated frequency components. Since its closed-form solution is not readily available, we alternatively derive closed-form expressions for corresponding upper and lower bounds. Three new speech enhancement estimators are proposed based on those bounds: one for each bound and one that is a combination of both. Results of PESQ and informal listening experiments indicate that the proposed estimators give better performances than earlier estimators.

  • Generalized Bayesian Estimators of the Spectral Amplitude for Speech Enhancement
    IEEE Signal Processing Letters, 2009
    Co-Authors: Eric Plourde, Benoit Champagne
    Abstract:

    In this letter, we show that many existing short-time Spectral Amplitude (STSA) Bayesian estimators for speech enhancement all have a similarly structured cost function. On this basis, we propose a new cost function that generalizes those of existent Bayesian STSA estimators and then obtain the corresponding closed-form solution for the optimal clean speech STSA. The resulting family of estimators, which we will term the generalized weighted family of STSA estimators (GWSA), features a new parameter that acts only on the estimated clean speech STSA. It is found that this new parameter yields an added flexibility in terms of achievable gain curves when compared to those of existing estimators. Moreover, we show that the new estimator family tends to a Wiener filter for high instantaneous signal-to-noise ratios.

  • Auditory-Based Spectral Amplitude Estimators for Speech Enhancement
    IEEE Transactions on Audio Speech and Language Processing, 2008
    Co-Authors: Eric Plourde, Benoit Champagne
    Abstract:

    We propose a new family of Bayesian estimators for speech enhancement where the cost function includes both a power law and a weighting factor. The parameters of the cost function, and therefore of the corresponding estimator gain, are chosen based on characteristics of the human auditory system, namely, the compressive nonlinearities of the cochlea, the perceived loudness and the ear's masking properties. It is found that choosing the parameters in this way results in a decrease of the estimator gain at high frequencies. This frequency dependence of the gain improves the noise reduction while limiting the speech distortion. Experimental results show that the new estimators achieve better enhancement performance than existing Bayesian estimators such as those based on the minimum mean-square error (MMSE) of the short-time Spectral Amplitude (STSA), the MMSE of the logarithm of the STSA (LSA) or the weighted euclidien (WE) error, both in terms of objective and subjective measures.

Marek B. Trawicki - One of the best experts on this subject based on the ideXlab platform.

  • distributed multichannel speech enhancement with minimum mean square error short time Spectral Amplitude log Spectral Amplitude and Spectral phase estimation
    Signal Processing, 2012
    Co-Authors: Marek B. Trawicki, Michael T Johnson
    Abstract:

    In this paper, the authors present optimal multichannel frequency domain estimators for minimum mean-square error (MMSE) short-time Spectral Amplitude (STSA), log-Spectral Amplitude (LSA), and Spectral phase estimation in a widely distributed microphone configuration. The estimators utilize Rayleigh and Gaussian statistical models for the speech prior and noise likelihood with a diffuse noise field for the surrounding environment. Based on the Signal-to-Noise Ratio (SNR) and Segmental Signal-to-Noise Ratio (SSNR) along with the Log-Likelihood Ratio (LLR) and Perceptual Evaluation of Speech Quality (PESQ) as objective metrics, the multichannel LSA estimator decreases background noise and speech distortion and increases speech quality compared to the baseline single channel STSA and LSA estimators, where the optimal multichannel Spectral phase estimator serves as a significant quantity to the improvements, and demonstrates robustness due to time alignment and attenuation factor estimation. Overall, the optimal distributed microphone Spectral estimators show strong results in noisy environments with application to many consumer, industrial, and military products.

  • Distributed multichannel speech enhancement with minimum mean-square error short-time Spectral Amplitude, log-Spectral Amplitude, and Spectral phase estimation
    Signal Processing, 2012
    Co-Authors: Marek B. Trawicki, Michael T Johnson
    Abstract:

    In this paper, the authors present optimal multichannel frequency domain estimators for minimum mean-square error (MMSE) short-time Spectral Amplitude (STSA), log-Spectral Amplitude (LSA), and Spectral phase estimation in a widely distributed microphone configuration. The estimators utilize Rayleigh and Gaussian statistical models for the speech prior and noise likelihood with a diffuse noise field for the surrounding environment. Based on the Signal-to-Noise Ratio (SNR) and Segmental Signal-to-Noise Ratio (SSNR) along with the Log-Likelihood Ratio (LLR) and Perceptual Evaluation of Speech Quality (PESQ) as objective metrics, the multichannel LSA estimator decreases background noise and speech distortion and increases speech quality compared to the baseline single channel STSA and LSA estimators, where the optimal multichannel Spectral phase estimator serves as a significant quantity to the improvements, and demonstrates robustness due to time alignment and attenuation factor estimation. Overall, the optimal distributed microphone Spectral estimators show strong results in noisy environments with application to many consumer, industrial, and military products. © 2011 Elsevier B.V. All Rights Reserved.

  • INTERSPEECH - Improvements of the Beta-Order Minimum Mean-Square Error (MMSE) Spectral Amplitude Estimator using Chi Priors
    2012
    Co-Authors: Marek B. Trawicki, Michael T Johnson
    Abstract:

    In this paper, the authors propose the Beta-Order Minimum Mean-Square Error (MMSE) Spectral Amplitude estimator with Chi statistical models for the speech priors. The new estimator incorporates both a shape parameter on the distribution and cost function parameter. The performance of the MMSE Beta-Order Spectral Amplitude estimator with Chi speech prior is evaluated using the Segmental Signal-to-Noise Ratio (SSNR) and Perceptual Evaluation of Speech Quality (PESQ) objective quality measures. From the experimental results, the new estimator provides gains of 0-3 dB and 0-0.3 in SSNR and PESQ improvements over the corresponding MMSE Beta-Order MMSE Spectral Amplitude estimator with the standard Rayleigh statistical models for the speech prior.