In this work, we address the problem of estimating the a priori SNR for single-channel speech enhancement. Similar to the decision-directed (DD) approach we linearly combine the maximum likelihood estimate of the current a priori SNR with an estimate obtained from the previous frame. Based on the harmonic model for voiced speech we propose to smooth the a priori SNR estimate along harmonic trajectories instead of fixed discrete Fourier transform frequency bins. We interpolate from fixed DFT frequencies to harmonic frequencies by using a pitch-adaptive zero-padding in the time domain. The resulting pitch-adaptive decision-directed (PADDi) method increases the noise attenuation compared to the classical decision-directed approach and outperforms benchmark methods in terms of speech enhancement performance for several noise types at different SNRs, quantified by objective evaluation criteria.