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Improving a Multiple Pitch Estimation Method With AR Models
Multiple pitch estimation (MPE) methods aim to detect the pitches of the sounds that are part of a certain mixture. A possible approach to such problem is applying a FIR filter bank in the frequency domain and choosing the filter that presents more energy. This process is equivalent to performing a linear combination of frequency domain representations of a signal, hence it is a linear classification tool. When spectral lobes corresponding to existing partials merge, such process may fail. In this paper, AR models were used to provide an spectral representation where lobes tend to merge less. The proper choice of model significantly improved the MPE method.
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