The Experts below are selected from a list of 225 Experts worldwide ranked by ideXlab platform

Tokunbo Ogunfunmi - One of the best experts on this subject based on the ideXlab platform.

  • ACSSC - Performance enhanced scalable wideband Speech Coding for IP networks
    2014 48th Asilomar Conference on Signals Systems and Computers, 2014
    Co-Authors: Koji Seto, Tokunbo Ogunfunmi
    Abstract:

    The scalable wideband Speech Coding Scheme based on the internet low bitrate codec (iLBC) was previously presented and achieved Speech quality equivalent to ITU-T G.729.1 at high bit rates. However, the performance was limited at low bit rates. In this paper, we present various approaches to improve performance especially at low bit rates. In particular, the time-domain bandwidth extension (TDBWE) is employed for higher-band Coding, and the efficient Coding structure is employed in enhancement layers. The performance evaluation results show that significant improvement is achieved at low bit rates and the proposed codec outperforms G.729.1 at most bit rates.

  • Packet-loss robust scalable Speech Coding using the discrete wavelet transform
    2014 IEEE International Symposium on Circuits and Systems (ISCAS), 2014
    Co-Authors: Koji Seto, Tokunbo Ogunfunmi
    Abstract:

    This paper presents a new scalable Speech codec for IP networks using the discrete wavelet transform (DWT). The scalable narrowband Speech Coding Scheme based on the internet low bitrate codec (iLBC) was previously presented and achieved Speech quality equivalent to G.718 for narrowband signals. Whereas the performance of the core layer was satisfactory, the higher Speech quality by the addition of the enhancement layer which employed the modified discrete cosine transform (MDCT) was desired. We propose the utilization of the DWT instead of the MDCT to encode the core-layer Coding error in the enhancement layer. The experimental simulation results show that the DWT is a promising technique to use for enCoding highly non-stationary signals such as the Coding error.

  • ISCAS - Packet-loss robust scalable Speech Coding using the discrete wavelet transform
    2014 IEEE International Symposium on Circuits and Systems (ISCAS), 2014
    Co-Authors: Koji Seto, Tokunbo Ogunfunmi
    Abstract:

    This paper presents a new scalable Speech codec for IP networks using the discrete wavelet transform (DWT). The scalable narrowband Speech Coding Scheme based on the internet low bitrate codec (iLBC) was previously presented and achieved Speech quality equivalent to G.718 for narrowband signals. Whereas the performance of the core layer was satisfactory, the higher Speech quality by the addition of the enhancement layer which employed the modified discrete cosine transform (MDCT) was desired. We propose the utilization of the DWT instead of the MDCT to encode the core-layer Coding error in the enhancement layer. The experimental simulation results show that the DWT is a promising technique to use for enCoding highly non-stationary signals such as the Coding error.

  • Performance enhanced scalable wideband Speech Coding for IP networks
    2014 48th Asilomar Conference on Signals Systems and Computers, 2014
    Co-Authors: Koji Seto, Tokunbo Ogunfunmi
    Abstract:

    The scalable wideband Speech Coding Scheme based on the Internet low bitrate codec (iLBC) was previously presented and achieved Speech quality equivalent to ITU-T G.729.1 at high bit rates. However, the performance was limited at low bit rates. In this paper, we present various approaches to improve performance especially at low bit rates. In particular, the time-domain bandwidth extension (TDBWE) is employed for higher-band Coding, and the efficient Coding structure is employed in enhancement layers. The performance evaluation results show that significant improvement is achieved at low bit rates and the proposed codec outperforms G.729.1 at most bit rates.

V. Cuperman - One of the best experts on this subject based on the ideXlab platform.

  • Spectral magnitude quantization based on linear transforms for 4 kb/s Speech Coding
    2001 IEEE International Conference on Acoustics Speech and Signal Processing. Proceedings (Cat. No.01CH37221), 2001
    Co-Authors: C.o. Etemoglu, V. Cuperman
    Abstract:

    This paper presents a matching pursuits sinusoidal Speech coder which incorporates new techniques including a novel vector quantization (VQ) technique used for the weighted quantization of spectral magnitude vector, and an interframe quantization of spectral magnitudes using an interpolation matrix that minimize the weighted interpolation error. The paper describes a novel vector quantization technique, wherein the quantized vector is obtained by applying a linear transformation selected from a first codebook to a codevector selected from a second codebook. The transformation is selected from a family of linear transformations, represented by a matrix codebook. Vectors in the second codebook are called residual codevectors. In order to avoid high complexity during the search for the best linear transformation, each linear transformation is assigned a representative vector, such that the search can be done employing the representative vectors. The VQ design algorithm is based on joint optimization of the linear transformation and the residual codebooks. The introduced techniques are general enough to be used in any sinusoidal Speech Coding Scheme. In this work we incorporated the techniques into the matching pursuits sinusoidal model to achieve high quality Speech using sinusoidal Speech coder at 4 kbps. Subjective tests indicate that the proposed Coding model at 4 kbps has quality comparable to that of G.729 at 8 kbps.

  • ICASSP - Spectral magnitude quantization based on linear transforms for 4 kb/s Speech Coding
    2001 IEEE International Conference on Acoustics Speech and Signal Processing. Proceedings (Cat. No.01CH37221), 2001
    Co-Authors: C.o. Etemoglu, V. Cuperman
    Abstract:

    This paper presents a matching pursuits sinusoidal Speech coder which incorporates new techniques including a novel vector quantization (VQ) technique used for the weighted quantization of spectral magnitude vector, and an interframe quantization of spectral magnitudes using an interpolation matrix that minimize the weighted interpolation error. The paper describes a novel vector quantization technique, wherein the quantized vector is obtained by applying a linear transformation selected from a first codebook to a codevector selected from a second codebook. The transformation is selected from a family of linear transformations, represented by a matrix codebook. Vectors in the second codebook are called residual codevectors. In order to avoid high complexity during the search for the best linear transformation, each linear transformation is assigned a representative vector, such that the search can be done employing the representative vectors. The VQ design algorithm is based on joint optimization of the linear transformation and the residual codebooks. The introduced techniques are general enough to be used in any sinusoidal Speech Coding Scheme. In this work we incorporated the techniques into the matching pursuits sinusoidal model to achieve high quality Speech using sinusoidal Speech coder at 4 kbps. Subjective tests indicate that the proposed Coding model at 4 kbps has quality comparable to that of G.729 at 8 kbps.

Koji Seto - One of the best experts on this subject based on the ideXlab platform.

  • ACSSC - Performance enhanced scalable wideband Speech Coding for IP networks
    2014 48th Asilomar Conference on Signals Systems and Computers, 2014
    Co-Authors: Koji Seto, Tokunbo Ogunfunmi
    Abstract:

    The scalable wideband Speech Coding Scheme based on the internet low bitrate codec (iLBC) was previously presented and achieved Speech quality equivalent to ITU-T G.729.1 at high bit rates. However, the performance was limited at low bit rates. In this paper, we present various approaches to improve performance especially at low bit rates. In particular, the time-domain bandwidth extension (TDBWE) is employed for higher-band Coding, and the efficient Coding structure is employed in enhancement layers. The performance evaluation results show that significant improvement is achieved at low bit rates and the proposed codec outperforms G.729.1 at most bit rates.

  • Packet-loss robust scalable Speech Coding using the discrete wavelet transform
    2014 IEEE International Symposium on Circuits and Systems (ISCAS), 2014
    Co-Authors: Koji Seto, Tokunbo Ogunfunmi
    Abstract:

    This paper presents a new scalable Speech codec for IP networks using the discrete wavelet transform (DWT). The scalable narrowband Speech Coding Scheme based on the internet low bitrate codec (iLBC) was previously presented and achieved Speech quality equivalent to G.718 for narrowband signals. Whereas the performance of the core layer was satisfactory, the higher Speech quality by the addition of the enhancement layer which employed the modified discrete cosine transform (MDCT) was desired. We propose the utilization of the DWT instead of the MDCT to encode the core-layer Coding error in the enhancement layer. The experimental simulation results show that the DWT is a promising technique to use for enCoding highly non-stationary signals such as the Coding error.

  • ISCAS - Packet-loss robust scalable Speech Coding using the discrete wavelet transform
    2014 IEEE International Symposium on Circuits and Systems (ISCAS), 2014
    Co-Authors: Koji Seto, Tokunbo Ogunfunmi
    Abstract:

    This paper presents a new scalable Speech codec for IP networks using the discrete wavelet transform (DWT). The scalable narrowband Speech Coding Scheme based on the internet low bitrate codec (iLBC) was previously presented and achieved Speech quality equivalent to G.718 for narrowband signals. Whereas the performance of the core layer was satisfactory, the higher Speech quality by the addition of the enhancement layer which employed the modified discrete cosine transform (MDCT) was desired. We propose the utilization of the DWT instead of the MDCT to encode the core-layer Coding error in the enhancement layer. The experimental simulation results show that the DWT is a promising technique to use for enCoding highly non-stationary signals such as the Coding error.

  • Performance enhanced scalable wideband Speech Coding for IP networks
    2014 48th Asilomar Conference on Signals Systems and Computers, 2014
    Co-Authors: Koji Seto, Tokunbo Ogunfunmi
    Abstract:

    The scalable wideband Speech Coding Scheme based on the Internet low bitrate codec (iLBC) was previously presented and achieved Speech quality equivalent to ITU-T G.729.1 at high bit rates. However, the performance was limited at low bit rates. In this paper, we present various approaches to improve performance especially at low bit rates. In particular, the time-domain bandwidth extension (TDBWE) is employed for higher-band Coding, and the efficient Coding structure is employed in enhancement layers. The performance evaluation results show that significant improvement is achieved at low bit rates and the proposed codec outperforms G.729.1 at most bit rates.

C.o. Etemoglu - One of the best experts on this subject based on the ideXlab platform.

  • Spectral magnitude quantization based on linear transforms for 4 kb/s Speech Coding
    2001 IEEE International Conference on Acoustics Speech and Signal Processing. Proceedings (Cat. No.01CH37221), 2001
    Co-Authors: C.o. Etemoglu, V. Cuperman
    Abstract:

    This paper presents a matching pursuits sinusoidal Speech coder which incorporates new techniques including a novel vector quantization (VQ) technique used for the weighted quantization of spectral magnitude vector, and an interframe quantization of spectral magnitudes using an interpolation matrix that minimize the weighted interpolation error. The paper describes a novel vector quantization technique, wherein the quantized vector is obtained by applying a linear transformation selected from a first codebook to a codevector selected from a second codebook. The transformation is selected from a family of linear transformations, represented by a matrix codebook. Vectors in the second codebook are called residual codevectors. In order to avoid high complexity during the search for the best linear transformation, each linear transformation is assigned a representative vector, such that the search can be done employing the representative vectors. The VQ design algorithm is based on joint optimization of the linear transformation and the residual codebooks. The introduced techniques are general enough to be used in any sinusoidal Speech Coding Scheme. In this work we incorporated the techniques into the matching pursuits sinusoidal model to achieve high quality Speech using sinusoidal Speech coder at 4 kbps. Subjective tests indicate that the proposed Coding model at 4 kbps has quality comparable to that of G.729 at 8 kbps.

  • ICASSP - Spectral magnitude quantization based on linear transforms for 4 kb/s Speech Coding
    2001 IEEE International Conference on Acoustics Speech and Signal Processing. Proceedings (Cat. No.01CH37221), 2001
    Co-Authors: C.o. Etemoglu, V. Cuperman
    Abstract:

    This paper presents a matching pursuits sinusoidal Speech coder which incorporates new techniques including a novel vector quantization (VQ) technique used for the weighted quantization of spectral magnitude vector, and an interframe quantization of spectral magnitudes using an interpolation matrix that minimize the weighted interpolation error. The paper describes a novel vector quantization technique, wherein the quantized vector is obtained by applying a linear transformation selected from a first codebook to a codevector selected from a second codebook. The transformation is selected from a family of linear transformations, represented by a matrix codebook. Vectors in the second codebook are called residual codevectors. In order to avoid high complexity during the search for the best linear transformation, each linear transformation is assigned a representative vector, such that the search can be done employing the representative vectors. The VQ design algorithm is based on joint optimization of the linear transformation and the residual codebooks. The introduced techniques are general enough to be used in any sinusoidal Speech Coding Scheme. In this work we incorporated the techniques into the matching pursuits sinusoidal model to achieve high quality Speech using sinusoidal Speech coder at 4 kbps. Subjective tests indicate that the proposed Coding model at 4 kbps has quality comparable to that of G.729 at 8 kbps.

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

  • EUSIPCO - Wide-band Speech Coding using kernel methods and bandwidth extension based on parametric stereo
    2012
    Co-Authors: Gh. Alipoor, M. H. Savoji
    Abstract:

    A novel wide-band Speech Coding Scheme is developed, in this paper, based on kernel methods and bandwidth extension. The KLMS algorithm, a kernelized version of the well-known LMS algorithm, is employed in the framework of the backward ADPCM technique for enCoding the narrow-band part of the wide-band Speech. Simulation results show that utilizing this nonlinear method results in an average improvement of up to 3.4 dB in the SNR and 0.28 in the PESQ measure of the decoded Speech. The resultant narrow-band codec is subsequently extended to the wide-band Speech using a novel bandwidth extension technique inspired by the parametric stereo Coding. It is shown that the KLMS algorithm is also effective in this framework. This leads to a wide-band Speech Coding Scheme built on the nonlinear narrow-band codec at the extra cost of a small increase in the bite rate.

  • Wide-band Speech Coding based on bandwidth extension and sparse linear prediction
    2012 35th International Conference on Telecommunications and Signal Processing (TSP), 2012
    Co-Authors: Gh. Alipoor, M. H. Savoji
    Abstract:

    A novel wide-band Speech Coding Scheme based on bandwidth extension and sparse linear prediction is proposed in this paper. Bandwidth extension utilizes the correlation that exists between the low and high frequency parts of the wide-band Speech signal to regenerate, at the decoder, the high frequency components using the decoded low band signal. This leads to a wide-band Speech Coding Scheme built on a narrow-band codec at the extra cost of a small increase in the bite rate. Two successful narrow-band Coding structures are considered here for this purpose, namely Multi-Pulse Excitation (MPE) and Algebraic Code Excited Linear Prediction (ACELP), in conjunction with the recently introduced sparse linear prediction. Our tests confirm the usefulness of this new prediction technique for narrow-band Speech Coding. Moreover, a well-posed formulation is derived that significantly decreases the computational complexity and makes it possible to solve the sparse linear prediction problem within a reasonable complexity.

  • TSP - Wide-band Speech Coding based on bandwidth extension and sparse linear prediction
    2012 35th International Conference on Telecommunications and Signal Processing (TSP), 2012
    Co-Authors: Gh. Alipoor, M. H. Savoji
    Abstract:

    A novel wide-band Speech Coding Scheme based on bandwidth extension and sparse linear prediction is proposed in this paper. Bandwidth extension utilizes the correlation that exists between the low and high frequency parts of the wide-band Speech signal to regenerate, at the decoder, the high frequency components using the decoded low band signal. This leads to a wide-band Speech Coding Scheme built on a narrow-band codec at the extra cost of a small increase in the bite rate. Two successful narrow-band Coding structures are considered here for this purpose, namely Multi-Pulse Excitation (MPE) and Algebraic Code Excited Linear Prediction (ACELP), in conjunction with the recently introduced sparse linear prediction. Our tests confirm the usefulness of this new prediction technique for narrow-band Speech Coding. Moreover, a well-posed formulation is derived that significantly decreases the computational complexity and makes it possible to solve the sparse linear prediction problem within a reasonable complexity.

  • Wide-band Speech Coding using kernel methods and bandwidth extension based on parametric stereo
    2012 Proceedings of the 20th European Signal Processing Conference (EUSIPCO), 2012
    Co-Authors: Gh. Alipoor, M. H. Savoji
    Abstract:

    A novel wide-band Speech Coding Scheme is developed, in this paper, based on kernel methods and bandwidth extension. The KLMS algorithm, a kernelized version of the well-known LMS algorithm, is employed in the framework of the backward ADPCM technique for enCoding the narrow-band part of the wide-band Speech. Simulation results show that utilizing this nonlinear method results in an average improvement of up to 3.4 dB in the SNR and 0.28 in the PESQ measure of the decoded Speech. The resultant narrow-band codec is subsequently extended to the wide-band Speech using a novel bandwidth extension technique inspired by the parametric stereo Coding. It is shown that the KLMS algorithm is also effective in this framework. This leads to a wide-band Speech Coding Scheme built on the nonlinear narrow-band codec at the extra cost of a small increase in the bite rate.