APPLICATIONS OF SIGNAL ANALYSIS USING AUTOREGRESSIVE MODELS FOR AMPLITUDE MODULATION
| Type of publication: | Idiap-RR |
| Citation: | Ganapathy_Idiap-RR-35-2009 |
| Number: | Idiap-RR-35-2009 |
| Year: | 2009 |
| Month: | 12 |
| 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. |
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| Projects |
Idiap AMIDA DIRAC IM2 |
| Authors | |
| Added by: | [ADM] |
| Total mark: | 0 |
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