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@TECHREPORT{Ganapathy_Idiap-RR-35-2009,
         author = {Ganapathy, Sriram and Thomas, Samuel and Motlicek, Petr and Hermansky, Hynek},
       projects = {Idiap, AMIDA, DIRAC, IM2},
          month = {12},
          title = {APPLICATIONS OF SIGNAL ANALYSIS USING AUTOREGRESSIVE MODELS FOR AMPLITUDE MODULATION},
           type = {Idiap-RR},
         number = {Idiap-RR-35-2009},
           year = {2009},
    institution = {Idiap},
        address = {Rue Marconi 19},
       abstract = {Frequency Domain Linear Prediction (FDLP) represents an efficient technique for representing the long-term amplitude modulations (AM) of speech/audio signals using autoregressive models. For the proposed analysis technique, relatively long temporal segments (1000 ms) of the input signal are decomposed into a set of sub-bands. FDLP is applied on each sub-band to model the temporal envelopes. The residual of the linear prediction represents the frequency modulations (FM) in the sub-band signal. In this paper, we present several applications of the proposed AM-FM decomposition technique for a variety of tasks like wide-band audio coding,
speech recognition in reverberant environments and robust feature extraction for phoneme recognition.},
            pdf = {https://publications.idiap.ch/attachments/reports/2009/Ganapathy_Idiap-RR-35-2009.pdf}
}