  Bayesian parameter estimation of gravitational waves from compact binary
coalescence (CBC) typically requires more than millions of evaluations of
computationally expensive template waveforms. We propose a technique to reduce
the cost of waveform generation by exploiting the chirping behavior of CBC
signal. Our technique does not require waveforms at all frequencies in the
frequency range used in the analysis, and does not suffer from the fixed cost
due to the upsampling of waveforms. Our technique speeds up the parameter
estimation of typical binary neutron star signal by a factor of
$\mathcal{O}(10)$ for the low-frequency cutoff of $20\,\mathrm{Hz}$, and
$\mathcal{O}(10^2)$ for $5\,\mathrm{Hz}$. It does not require any offline
preparations or accurate estimates of source parameters provided by detection
pipelines.
