The Experts below are selected from a list of 276 Experts worldwide ranked by ideXlab platform

Sridha Sridharan - One of the best experts on this subject based on the ideXlab platform.

  • Speech Compression with preservation of speaker identity
    1997 IEEE International Conference on Acoustics Speech and Signal Processing, 1997
    Co-Authors: J. Leis, M. Phythian, Sridha Sridharan
    Abstract:

    Although much effort has been directed recently towards Speech Compression at rates below 4 kb/s, the primary metric for comparison has, understandably, been the amount of spectral distortion in the decompressed Speech. However, an aspect which is becoming important in some applications is the ability to identify the original speaker from the coded Speech algorithmically. We investigate here the effect of Speech Compression using multistage vector quantization of the short-term (formant) filter parameters on text-independent speaker identification. It is demonstrated that in cases where the Speech is stored in a compressed database for retrieval, the speaker model should be constructed from the raw Speech before spectral Compression. Additionally, Gaussian models of sufficiently high order are able to reduce the negative effects of spectral vector quantization upon speaker identification accuracy.

  • ICASSP - Speech Compression with preservation of speaker identity
    1997 IEEE International Conference on Acoustics Speech and Signal Processing, 1997
    Co-Authors: J. Leis, M. Phythian, Sridha Sridharan
    Abstract:

    Although much effort has been directed recently towards Speech Compression at rates below 4 kb/s, the primary metric for comparison has, understandably, been the amount of spectral distortion in the decompressed Speech. However, an aspect which is becoming important in some applications is the ability to identify the original speaker from the coded Speech algorithmically. We investigate here the effect of Speech Compression using multistage vector quantization of the short-term (formant) filter parameters on text-independent speaker identification. It is demonstrated that in cases where the Speech is stored in a compressed database for retrieval, the speaker model should be constructed from the raw Speech before spectral Compression. Additionally, Gaussian models of sufficiently high order are able to reduce the negative effects of spectral vector quantization upon speaker identification accuracy.

Adnane Cherif - One of the best experts on this subject based on the ideXlab platform.

  • New algorithm for QMF Banks Design and Its Application in Speech Compression using DWT
    The International Arab Journal of Information Technology, 2020
    Co-Authors: Noureddine Aloui, Chafik Barnoussi, Adnane Cherif
    Abstract:

    This paper presents a new algorithm for designing Quadrature Mirrors Filters (QMF) banks using windowing techniques. In the proposed algorithm the cut off frequency of the prototype filters is iteratively varied such that the perfect reconstruction at frequency (ω=0.5π) in ideal condition is approximately equal to 0.707. The designed QMF banks are used as mother wavelet for Speech Compression algorithm based on Discrete Wavelet Transform (DWT). The evaluation tests prove the efficiency of the proposed algorithm in Speech Compression using wavelets. The comparison results between the proposed algorithms with other existing algorithms used for designing QMF banks show an important reduction in Reconstruction Error (RE) and number of iterations.

  • optimized Speech Compression algorithm based on wavelets techniques and its real time implementation on dsp
    International Journal of Information Technology and Computer Science, 2015
    Co-Authors: Noureddine Aloui, Souha Bousselmi, Adnane Cherif
    Abstract:

    This paper presents an optimized Speech Compression algorithm using discrete wavelet transform, and its real time implementation on fixed-point digital signal processor (DSP). The optimized Speech Compression algorithm presents the advantages to ensure low complexity, low bit rate and achieve high Speech coding efficiency, and this by adding a voice activity detector (VAD) module before the application of the discrete wavelet transform. The VAD module avoids the computation of the discrete wavelet coefficients during the inactive voice signal. In addition, a real-time implementation of the optimized Speech Compression algorithm is performed using fixed-point processor. The optimized and the original algorithms are evaluated and compared in terms of CPU time (sec), Cycle count (MCPS), Memory consumption (Ko), Compression Ratio (CR), Signal to Noise Ratio (SNR), Peak Signal to Noise Ratio (PSNR) and Normalized Root Mean Square Error (NRMSE).

  • Genetic Algorithm For Designing QMF Banks and Its Application In Speech Compression Using Wavelets
    International Journal of Image Graphics and Signal Processing, 2013
    Co-Authors: Noureddine Aloui, Ben Nasr Mohamed, Adnane Cherif
    Abstract:

    In this paper, real-coded genetic algorithm (GA) is used for designing two-channel quadrature mirror filter (QMF) banks based on the Kaiser Window. The shape of the Kaiser window and the cutoff frequency of the prototype filter are optimized using a simple GA. The optimized QMF banks are exploited as mother wavelets for Speech Compression based on discret wavelet transform (DWT). The simulation results show the efficiency of the GA for designing QMF banks using adjustable windows length and especially for optimizing wavelet filters used in Speech Compression based on wavelets. In addition, a comparative of performance of the developed wavelets filters using GA and others known wavelets is made in term of objective criteria (CR, SNR, PSNR, and NRMSE). The simulation results show that the optimized wavelets filters outperform others wavelets already exist used for Speech Compression.

J. Leis - One of the best experts on this subject based on the ideXlab platform.

  • Speech Compression with preservation of speaker identity
    1997 IEEE International Conference on Acoustics Speech and Signal Processing, 1997
    Co-Authors: J. Leis, M. Phythian, Sridha Sridharan
    Abstract:

    Although much effort has been directed recently towards Speech Compression at rates below 4 kb/s, the primary metric for comparison has, understandably, been the amount of spectral distortion in the decompressed Speech. However, an aspect which is becoming important in some applications is the ability to identify the original speaker from the coded Speech algorithmically. We investigate here the effect of Speech Compression using multistage vector quantization of the short-term (formant) filter parameters on text-independent speaker identification. It is demonstrated that in cases where the Speech is stored in a compressed database for retrieval, the speaker model should be constructed from the raw Speech before spectral Compression. Additionally, Gaussian models of sufficiently high order are able to reduce the negative effects of spectral vector quantization upon speaker identification accuracy.

  • ICASSP - Speech Compression with preservation of speaker identity
    1997 IEEE International Conference on Acoustics Speech and Signal Processing, 1997
    Co-Authors: J. Leis, M. Phythian, Sridha Sridharan
    Abstract:

    Although much effort has been directed recently towards Speech Compression at rates below 4 kb/s, the primary metric for comparison has, understandably, been the amount of spectral distortion in the decompressed Speech. However, an aspect which is becoming important in some applications is the ability to identify the original speaker from the coded Speech algorithmically. We investigate here the effect of Speech Compression using multistage vector quantization of the short-term (formant) filter parameters on text-independent speaker identification. It is demonstrated that in cases where the Speech is stored in a compressed database for retrieval, the speaker model should be constructed from the raw Speech before spectral Compression. Additionally, Gaussian models of sufficiently high order are able to reduce the negative effects of spectral vector quantization upon speaker identification accuracy.

Noureddine Aloui - One of the best experts on this subject based on the ideXlab platform.

  • New algorithm for QMF Banks Design and Its Application in Speech Compression using DWT
    The International Arab Journal of Information Technology, 2020
    Co-Authors: Noureddine Aloui, Chafik Barnoussi, Adnane Cherif
    Abstract:

    This paper presents a new algorithm for designing Quadrature Mirrors Filters (QMF) banks using windowing techniques. In the proposed algorithm the cut off frequency of the prototype filters is iteratively varied such that the perfect reconstruction at frequency (ω=0.5π) in ideal condition is approximately equal to 0.707. The designed QMF banks are used as mother wavelet for Speech Compression algorithm based on Discrete Wavelet Transform (DWT). The evaluation tests prove the efficiency of the proposed algorithm in Speech Compression using wavelets. The comparison results between the proposed algorithms with other existing algorithms used for designing QMF banks show an important reduction in Reconstruction Error (RE) and number of iterations.

  • optimized Speech Compression algorithm based on wavelets techniques and its real time implementation on dsp
    International Journal of Information Technology and Computer Science, 2015
    Co-Authors: Noureddine Aloui, Souha Bousselmi, Adnane Cherif
    Abstract:

    This paper presents an optimized Speech Compression algorithm using discrete wavelet transform, and its real time implementation on fixed-point digital signal processor (DSP). The optimized Speech Compression algorithm presents the advantages to ensure low complexity, low bit rate and achieve high Speech coding efficiency, and this by adding a voice activity detector (VAD) module before the application of the discrete wavelet transform. The VAD module avoids the computation of the discrete wavelet coefficients during the inactive voice signal. In addition, a real-time implementation of the optimized Speech Compression algorithm is performed using fixed-point processor. The optimized and the original algorithms are evaluated and compared in terms of CPU time (sec), Cycle count (MCPS), Memory consumption (Ko), Compression Ratio (CR), Signal to Noise Ratio (SNR), Peak Signal to Noise Ratio (PSNR) and Normalized Root Mean Square Error (NRMSE).

  • Genetic Algorithm For Designing QMF Banks and Its Application In Speech Compression Using Wavelets
    International Journal of Image Graphics and Signal Processing, 2013
    Co-Authors: Noureddine Aloui, Ben Nasr Mohamed, Adnane Cherif
    Abstract:

    In this paper, real-coded genetic algorithm (GA) is used for designing two-channel quadrature mirror filter (QMF) banks based on the Kaiser Window. The shape of the Kaiser window and the cutoff frequency of the prototype filter are optimized using a simple GA. The optimized QMF banks are exploited as mother wavelets for Speech Compression based on discret wavelet transform (DWT). The simulation results show the efficiency of the GA for designing QMF banks using adjustable windows length and especially for optimizing wavelet filters used in Speech Compression based on wavelets. In addition, a comparative of performance of the developed wavelets filters using GA and others known wavelets is made in term of objective criteria (CR, SNR, PSNR, and NRMSE). The simulation results show that the optimized wavelets filters outperform others wavelets already exist used for Speech Compression.

M. Phythian - One of the best experts on this subject based on the ideXlab platform.

  • Speech Compression with preservation of speaker identity
    1997 IEEE International Conference on Acoustics Speech and Signal Processing, 1997
    Co-Authors: J. Leis, M. Phythian, Sridha Sridharan
    Abstract:

    Although much effort has been directed recently towards Speech Compression at rates below 4 kb/s, the primary metric for comparison has, understandably, been the amount of spectral distortion in the decompressed Speech. However, an aspect which is becoming important in some applications is the ability to identify the original speaker from the coded Speech algorithmically. We investigate here the effect of Speech Compression using multistage vector quantization of the short-term (formant) filter parameters on text-independent speaker identification. It is demonstrated that in cases where the Speech is stored in a compressed database for retrieval, the speaker model should be constructed from the raw Speech before spectral Compression. Additionally, Gaussian models of sufficiently high order are able to reduce the negative effects of spectral vector quantization upon speaker identification accuracy.

  • ICASSP - Speech Compression with preservation of speaker identity
    1997 IEEE International Conference on Acoustics Speech and Signal Processing, 1997
    Co-Authors: J. Leis, M. Phythian, Sridha Sridharan
    Abstract:

    Although much effort has been directed recently towards Speech Compression at rates below 4 kb/s, the primary metric for comparison has, understandably, been the amount of spectral distortion in the decompressed Speech. However, an aspect which is becoming important in some applications is the ability to identify the original speaker from the coded Speech algorithmically. We investigate here the effect of Speech Compression using multistage vector quantization of the short-term (formant) filter parameters on text-independent speaker identification. It is demonstrated that in cases where the Speech is stored in a compressed database for retrieval, the speaker model should be constructed from the raw Speech before spectral Compression. Additionally, Gaussian models of sufficiently high order are able to reduce the negative effects of spectral vector quantization upon speaker identification accuracy.