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    TASLP
    2010
    157views more  TASLP 2010»
    HMM-Based Reconstruction of Unreliable Spectrographic Data for Noise Robust Speech Recognition
    13 years 2 months ago
    HMM-Based Reconstruction of Unreliable Spectrographic Data for Noise Robust Speech Recognition
    Download  www.ee.ucla.edu
    This paper presents a framework for efficient HMM-based estimation of unreliable spectrographic speech data. It discusses the role of Hidden Markov Models (HMMs) during minimum mea...
    Bengt J. Borgstrom, Abeer Alwan
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    TASLP
    2010
    117views more  TASLP 2010»
    Speech Enhancement Using Gaussian Scale Mixture Models
    13 years 2 months ago
    Speech Enhancement Using Gaussian Scale Mixture Models
    Download  papers.cnl.salk.edu
    This paper presents a novel probabilistic approach to speech enhancement. Instead of a deterministic logarithmic relationship, we assume a probabilistic relationship between the fr...
    Jiucang Hao, Te-Won Lee, Terrence J. Sejnowski
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    TASLP
    2010
    132views more  TASLP 2010»
    Using Reverberation to Improve Range and Elevation Discrimination for Small Array Sound Source Localization
    13 years 2 months ago
    Using Reverberation to Improve Range and Elevation Discrimination for Small Array Sound Source Localization
    Download  research.microsoft.com
    Sound source localization (SSL) is an essential task in many applications involving speech capture and enhancement. As such, speaker localization with microphone arrays has receive...
    Flavio Ribeiro, Cha Zhang, Dinei A. F. Florê...
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    TASLP
    2010
    167views more  TASLP 2010»
    Broadband Source Localization From an Eigenanalysis Perspective
    13 years 2 months ago
    Broadband Source Localization From an Eigenanalysis Perspective
    Download  externe.emt.inrs.ca
    Abstract--Broadband source localization has several applications ranging from automatic video camera steering to target signal tracking and enhancement through beamforming. Consequ...
    Mehrez Souden, Jacob Benesty, Sofiène Affes
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    TASLP
    2010
    138views more  TASLP 2010»
    Glimpsing IVA: A Framework for Overcomplete/Complete/Undercomplete Convolutive Source Separation
    13 years 2 months ago
    Glimpsing IVA: A Framework for Overcomplete/Complete/Undercomplete Convolutive Source Separation
    Download  dsp.ucsd.edu
    Abstract--Independent vector analysis (IVA) is a method for separating convolutedly mixed signals that significantly reduces the occurrence of the well-known permutation problem in...
    Alireza Masnadi-Shirazi, Wenyi Zhang, Bhaskar D. R...
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