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  • 1.
    Grancharov, Volodya
    et al.
    KTH, School of Electrical Engineering (EES), Sound and Image Processing.
    Plasberg, Jan H.
    KTH, School of Electrical Engineering (EES), Sound and Image Processing.
    Samuelsson, Jonas
    KTH, School of Electrical Engineering (EES), Sound and Image Processing.
    Kleijn, Bastiaan
    KTH, School of Electrical Engineering (EES), Sound and Image Processing.
    Generalized postfilter for speech quality enhancement2008In: IEEE Transactions on Audio, Speech and Language Processing, ISSN 1558-7916, Vol. 16, no 1, p. 57-64Article in journal (Refereed)
    Abstract [en]

    Postfilters are commonly used in speech coding for the attenuation of quantization noise. In the presence of acoustic background noise or distortion due to tandeming operations, the postfilter parameters are not adjusted and the performance is, therefore, not optimal. We propose a modification that consists of replacing the nonadaptive postfilter parameters with parameters that adapt to variations in spectral flatness, obtained from the noisy speech. This generalization of the postfiltering concept can handle a larger range of noise conditions, but has the same computational complexity and memory requirements as the conventional postfilter. Test results indicate that the presented algorithm improves on the standard postfilter, as well as on the combination of a noise attenuation preprocessor and the conventional postfilter.

  • 2.
    Lindblom, Jonas
    et al.
    KTH, School of Electrical Engineering (EES), Sound and Image Processing.
    Plasberg, Jan H
    KTH, School of Electrical Engineering (EES), Sound and Image Processing.
    Vafin, Renat
    KTH, School of Electrical Engineering (EES), Sound and Image Processing.
    Flexible sum-difference stereo coding based on time-aligned signal components2005In: 2005 WORKSHOP ON APPLICATIONS OF SIGNAL PROCESSING TO AUDIO AND ACOUSTICS (WASPAA), 2005, p. 255-258Conference paper (Refereed)
    Abstract [en]

    A framework for flexible and efficient coding of general stereo audio signals is proposed. Methods based on the framework can be used together with an arbitrary single channel (mono) coder to achieve seamless transition from pure parametric stereo coding to waveform approximating coding as the bitrate is increased. The idea, based on sum-difference encoding of time-aligned signal components, is presented as a general framework. An example implementation is demonstrated to have the desired convergence properties towards transparent quality.

  • 3.
    Plasberg, Jan H.
    et al.
    KTH, School of Electrical Engineering (EES), Sound and Image Processing.
    Kleijn, W. Bastiaan
    KTH, School of Electrical Engineering (EES), Sound and Image Processing.
    Complexity-constrained feature selection for classification: 2007 DIGEST OF TECHNICAL PAPERS INTERNATIONAL CONFERENCE ON CONSUMER ELECTRONICS2007In: IEEE ICCE, 2007, p. 9-10Conference paper (Refereed)
    Abstract [en]

    Continuous monitoring of audio-visual context on mobile devices requires algorithms with gentle demands on computational resources. Existing feature selection strategies for classification do not account for the complexity associated with feature extraction. We present a complexity-constrained feature selection algorithm that is independent of the classifier architecture and demonstrate that it leads to superior feature sets if the allowed computational complexity is limited.

  • 4.
    Plasberg, Jan H.
    et al.
    KTH, School of Electrical Engineering (EES), Sound and Image Processing.
    Kleijn, W. Bastiaan
    KTH, School of Electrical Engineering (EES), Sound and Image Processing.
    Feature Selection Under a Complexity Constraint2009In: IEEE transactions on multimedia, ISSN 1520-9210, E-ISSN 1941-0077, Vol. 11, no 3, p. 565-571Article in journal (Refereed)
    Abstract [en]

    Classification on mobile devices is often done in an uninterrupted fashion. This requires algorithms with gentle demands on the computational complexity. The performance of a classifier depends heavily on the set of features used as input variables. Existing feature selection strategies for classification aim at finding a "best" set of features that performs well in terms of classification accuracy, but are not designed to handle constraints on the computational complexity. We demonstrate that an extension of the performance measures used in state-of-the-art feature selection algorithms with a penalty on the feature extraction complexity leads to superior feature sets if the allowed computational complexity is limited. Our solution is independent of a particular classification algorithm.

  • 5.
    Plasberg, Jan H.
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Zhao, D. Y.
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Kleijn, W. B.
    KTH, School of Electrical Engineering (EES), Signal Processing.
    The sensitivity matrix for a spectro-temporal auditory model2015In: European Signal Processing Conference, European Signal Processing Conference, EUSIPCO , 2015, p. 1673-1676Conference paper (Refereed)
    Abstract [en]

    Perceptually optimal processing of speech and audio signals demands distortion measures that are based on sophisticated auditory models. High-rate theory can simplify these models by means of a sensitivity matrix. We present a method to derive the sensitivity matrix for distortion measures based on spectro-temporal auditory models under the assumption of small errors. This method is applied to an example auditory model and the region of validity of the approximation as well as a way to analyze the characteristics of the model with subspace methods are discussed.

  • 6.
    Samuelsson, Jonas
    et al.
    KTH, School of Electrical Engineering (EES), Sound and Image Processing. KTH, School of Information and Communication Technology (ICT), Centres, Center for Wireless Systems, Wireless@kth.
    Plasberg, Jan H.
    KTH, School of Electrical Engineering (EES), Sound and Image Processing. KTH, School of Information and Communication Technology (ICT), Centres, Center for Wireless Systems, Wireless@kth.
    Multiple description coding based on Gaussian mixture models2005In: IEEE Signal Processing Letters, ISSN 1070-9908, E-ISSN 1558-2361, Vol. 12, no 6, p. 449-452Article in journal (Refereed)
    Abstract [en]

    An algorithm for multiple description coding (MDC) based on Gaussian mixture models (GMMs) is presented. Based on the parameters of the GMM, the algorithm combines MDC scalar quantizers, yielding a source-optimized vector MDC system. The performance is evaluated on a speech spectrum source in terms of mean-squared error and log spectral distortion. It is demonstrated experimentally that the proposed system outperforms single description coding and repetition coding over a wide range of channel failure probabilities. The proposed algorithm has a complexity that is linear in rate and dimension while retaining a near optimal vector quantizer point density.

  • 7. van Schijndel, N. H.
    et al.
    Bensa, J.
    Christensen, M. G.
    Colomes, C.
    Edler, B.
    Heusdens, R.
    Jensen, J.
    Jensen, S. H.
    Kleijn, W. Bastiaan
    KTH, School of Electrical Engineering (EES), Sound and Image Processing.
    Kot, V.
    Kovesi, B.
    Lindblom, Jonas
    KTH, School of Electrical Engineering (EES), Sound and Image Processing.
    Massaloux, D.
    Niamut, O. A.
    Norden, F.
    Plasberg, Jan H.
    KTH, School of Electrical Engineering (EES), Sound and Image Processing.
    Vafin, Renat
    KTH, School of Electrical Engineering (EES), Sound and Image Processing.
    van de Par, S.
    Virette, D.
    Wubbolt, O.
    Adaptive RD Optimized Hybrid Sound Coding2008In: AES: Journal of the Audio Engineering Society, ISSN 1549-4950, Vol. 56, no 10, p. 787-809Article in journal (Refereed)
    Abstract [en]

    Traditionally, sound codecs have been developed with a particular application in mind, their performance being optimized for specific types of input signals, such as speech or audio (music), and application constraints, such as low bit rate, high quality, or low delay. There is, however, an increasing need for more generic sound codecs, created by the emergence of heterogeneous networks and the convergence of communication and entertainment devices. To obtain such versatility, this study employs hybrid sound coding based on operational rate-distortion (RD) optimization principles. Applying this concept, a prototype coder has been implemented with emphasis on (dynamic) adaptation to the input and to application constraints. With this prototype, listening tests have been performed for different application scenarios. The results demonstrate the versatility of the concept while keeping competitive sound quality compared to dedicated state-of-the-art codecs.

1 - 7 of 7
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